Please Introduce Yourself

I’m Oluwasesan Kayode Yackson, a senior software and DevOps engineer, entrepreneur, and Co-founder & Chief Operating Officer of ProtonLabs Technology Inc. I began my career in pharmacy, earning my bachelor’s degree before transitioning into software engineering and cloud infrastructure. Today, I combine scientific rigor, cloud infrastructure expertise, and operational leadership to build scalable, high-performance technology systems.

At ProtonLabs, I oversee our global cloud infrastructure, DevOps strategy, business operations, growth, and strategic partnerships. My focus is on making complex, high-scale AI infrastructure simple, resilient, and accessible so our products can reliably serve millions of users worldwide every day.

Can you tell us about ProtonLabs and the AI products you’ve built, including AskYourPDF, Cowriter.ai, Detect.ai and Simplicity.AI?

ProtonLabs is a UK-based AI company dedicated to developing practical solutions that simplify complex workflows and boost human productivity. We specialize in bridging the gap between frontier AI capability and everyday usability by building tools that fit directly into existing user workflows.

Our product portfolio includes:

• AskYourPDF: Our flagship document intelligence platform that allows users to extract insights, summarize research papers, and interact with complex documents via text, web extensions, mobile apps, and direct ChatGPT integrations.
• Cowriter.ai: An AI-assisted writing and deep research platform designed to help users produce high quality content and accelerate literature discovery.
• Detect.ai: An advanced AI-content detection tool built to help organizations and individuals verify content authenticity and maintain editorial integrity.
• Simplicity.AI: A smart AI form filler that converts static or scanned PDFs into interactive digital documents and auto-fills complex tax, legal, healthcare, employment, and immigration paperwork accurately in seconds.

ProtonLabs’ products now serve more than 5 million users worldwide. What do you think has been the biggest factor behind the company’s success and growth?

Our growth comes down to three core principles: solving real user pain points, moving with extreme execution speed, and taking distribution as seriously as engineering.

As a bootstrapped company, we鈥檝e always had to maintain operational discipline. We focus less on top-of funnel vanity metrics like sign-ups and more on customer retention, willingness to pay, and organic word of mouth.

From an infrastructure and product perspective, a major driver was our multi-surface distribution strategy. We didn鈥檛 force users to change their habits; instead, we met them where they were already working鈥� building integrations across the web, ChatGPT plugins, Chrome extensions, Zotero, mobile platforms, and robust APIs. When you combine high product utility with seamless distribution and high platform availability, organic growth naturally follows.

As a judge for SaaS66, what qualities will you be looking for when evaluating startups?

I am looking for companies that make complexity feel effortless. From an operational and technical standpoint, I will be evaluating four key areas:

• Clear Value Proposition: Can the founders explain in plain language who the customer is, what painful problem is being solved, and why their solution is significantly better than current alternatives?
• Technical Rigor & Reliability: Is the underlying cloud architecture built to scale securely, economically, and reliably as user demand grows?
• Distribution Clarity: Does the team have a clear, repeatable strategy for acquiring and retaining users without relying purely on paid marketing?
• Execution Speed: Can the founders demonstrate fast feedback loops between customer input and product iteration?

What separates a good SaaS business from a great one?

A good SaaS business builds a useful product, finds an initial customer base, and grows revenue by solving a visible problem. A great SaaS business builds a resilient, highly scalable system that becomes deeply embedded in the customer鈥檚 daily operations while maintaining relentless discipline around unit economics.

From an operational and technical standpoint, the differentiation comes down to four critical factors:

• Workflow Integration vs. Point Solutions: Good SaaS tools are nice-to-have utilities that live in an open tab. Great SaaS tools integrate directly into existing workflows鈥攙ia APIs, extensions, and ecosystem integrations鈥攎aking them essential and creating natural retention without forcing users to build entirely new habits.
• Unit Economics and Infrastructure Efficiency: Good companies scale revenue, but great companies scale margins. In AI and software engineering, managing cloud infrastructure costs, optimizing server operations, and ensuring high platform availability as traffic grows is what keeps gross margins healthy as you scale to millions of users.
• Retention Over Acquisition: Good SaaS focuses heavily on top-of-funnel sign-ups and marketing hype. Great SaaS focuses relentlessly on cohorts, usage depth, willingness to pay, and net revenue retention. If users aren’t coming back organically and recommending the product, growth is just an expensive illusion.
• Speed of the Feedback Loop: Good teams ship features on a schedule. Great teams shorten the loop between user feedback, system observability, and engineering deployment to continually refine the product based on how people actually use it every day.

What are the biggest mistakes you see SaaS founders making when trying to scale their businesses?

The most common mistakes I see stem from misaligned scaling priorities:

• Premature Scaling: Rushing to scale distribution, sales, or infrastructure before achieving true product-market fit and solid unit economics.
• Ignoring Distribution: Relying on the assumption that a technically superior product will sell itself. Technical founders must treat distribution and growth with the same architectural rigor as their codebase.
• Neglecting Cloud Cost & Architecture Efficiency: Overlooking infrastructure margins early on. In AI and SaaS, inefficient API usage or unoptimized cloud architecture can quickly ruin unit economics as user volume scales.
• Focusing on Attention Over Value: Confusing viral sign-ups with sustainable retention. If users don’t return or aren’t willing to pay, long-term growth will collapse.

If you could give one piece of advice to founders entering SaaS66 this year, what would it be?

Be remarkably concrete and lead with evidence.

Within your first couple of sentences, state clearly who you serve, the exact problem you solve, the measurable outcome you create, and how your approach is fundamentally different. Avoid vague jargon or long market histories.

Back up your story with hard metrics鈥攔etention, unit economics, customer outcomes, and growth trajectory. Finally, ensure you articulate your distribution model just as clearly as your technical architecture. Show us not only that you can build a great platform, but how you will get it into the hands of millions.

What are you most looking forward to seeing in the SaaS industry in the next few years?

I am most excited about the transition from isolated, chat-based AI tools into deeply embedded workflow automation engines.

We are moving past generic prompt-and-response setups toward autonomous, context-aware systems capable of retrieving complex data, executing background tasks across multiple tool stacks, and handing off work seamlessly to human operators when human oversight is required. Seeing these workflow advancements applied to heavy operational fields like legal, healthcare, logistics, document intelligence, and corporate administration represents a massive opportunity to redefine software productivity.

The post A Chat With Oluwasesan Kayode Yackson, Co-Founder And COO at ProtonLabs Technology Inc. Ltd. and 91探花 SaaS66 2026 Judge appeared first on 91探花.

When he began preparing to relocate back in 2026, he found that despite how much the country had changed, he found the relocation process as chaotic as ever: one answer in a Facebook group, another on WhatsApp, another through a recruiter, another on a government website, with the rest left to word of mouth. Housing, schools, jobs, banking, neighbourhoods, documentation and the basic questions of day-to-day life all sat in different places with no single source tying them together.

What struck him wasn’t a lack of information but a lack of trust, context and navigation, which raised an obvious question: why wasn’t there one intelligent platform that understood who someone was, why they were moving and what they actually needed, then guided them through the whole journey? That question became Ahlan.

We chatted to Abiel to find out more about how AI is being used to personalise relocation at scale, what he’s learned from Ahlan’s early beta users, and his ambitions for the platform beyond the UK-Saudi corridor.

2. For those unfamiliar with the company, what exactly does Ahlan do, and how does the platform simplify the relocation and settlement process for users?

Ahlan is an AI-powered global mobility and settlement platform, starting in Saudi Arabia.

The aim is to bring the whole relocation journey into one place. Users can get personalised guidance through Ask Ahlan, explore where to live, compare schools, discover jobs, access trusted providers, use personalised settlement checklists and connect with communities and local events.

Importantly, we’re also building transactional capability into the platform. Users will be able to book events, arrange short- and long-stay accommodation, make school enquiries and bookings and apply for jobs directly through Ahlan.

So rather than simply telling someone what they need to do, Ahlan is being built to help them actually complete the journey. The long-term idea is simple: someone should be able to go from “I’m considering moving to Saudi Arabia” to “I’m settled and thriving here” through one connected platform.

3. You describe Ahlan as an AI-powered global mobility and settlement platform. How is AI being used in practice, and what problems does it solve that traditional relocation services struggle with?

AI allows us to personalise relocation at scale. Instead of simply answering generic questions, Ahlan can understand the user’s circumstances and help guide them toward the most relevant options across housing, schools, jobs, services and local life.

For example, rather than someone asking “What are the best areas in Riyadh?”, Ahlan can eventually understand that they’re moving with children, working in a certain part of the city, have a particular budget and want to be close to a specific type of school.

That completely changes the usefulness of the answer. As the platform develops, that intelligence will sit alongside transactional features. So a user could receive personalised housing recommendations and then book short or long-term accommodation, discover a suitable school and progress that journey or identify a relevant job and apply through the Platform.

That combination of personalised intelligence and action is really important. Traditional relocation services are often manual and fragmented. Ahlan is being designed to connect guidance directly to the next step.

4. Saudi Arabia is undergoing significant economic and social transformation. How have these changes influenced demand for services like Ahlan?

The transformation in Saudi Arabia is a major part of why the timing is so interesting. The country is attracting international companies, investors, entrepreneurs, skilled professionals, educators and families on a scale that is very different from when I previously lived there.

At the same time, Saudi Arabia itself is changing quickly. New industries are growing, cities are developing, tourism is expanding and the lifestyle proposition for international residents is very different from even a decade ago. That creates a huge amount of opportunity, but it also creates complexity for someone who has never lived there.

The more international talent Saudi Arabia attracts, the more important the settlement experience becomes. Recruiting somebody is only the first step. They still need to understand where to live, where their children should go to school, how daily life works, how to build a community and how to navigate the country confidently. That’s the gap Ahlan is trying to address.

5. What are some of the biggest challenges international professionals and families face when moving to Saudi Arabia, and which misconceptions about relocating to the Kingdom do you encounter most often?

One of the biggest challenges is simply knowing what to trust. People receive conflicting advice from social media, friends, recruiters and online searches. And relocation decisions are highly personal, so what works for one person may be completely unsuitable for
another.

For families, schools and housing are usually major concerns. Professionals want to understand salaries, commute, neighbourhoods and career opportunities. Others worry about banking, documentation, healthcare, social life or simply what daily life will actually feel like.

There are also still a lot of outdated perceptions of Saudi Arabia. People who have never visited sometimes have an image of the country that’s years behind reality. When they arrive, many are surprised by how rapidly Riyadh and other cities have developed, the scale of international investment, the number of events and restaurants and how much the social environment has evolved.

That said, I think it’s important not to oversell relocation either. Every country has practical challenges. Ahlan’s role isn’t to market a fantasy. It’s to give people enough trusted information to make informed decisions and settle successfully.

6. Ahlan is currently live in beta with more than 350 users and 11 signed pilots. What have you learned from those early users, and how has their feedback shaped the platform?

The biggest lesson has been that people want more than information. They want a platform that helps them act on it.

Early behaviour has shown strong interest in jobs and careers, housing, schools, community and personalised guidance. That’s reinforced our decision to build deeper functionality around those areas.

We’re therefore developing Ahlan so users can move from discovery into action, including applying for jobs, booking events, arranging short- and long-stay accommodation and progressing school enquiries and bookings. We’re also adding employer profiles, because a large proportion of international mobility starts with employment. That allows us to connect employers, candidates and the wider settlement journey much more naturally.

The pilots are equally important because they allow us to test how schools, employers and service providers can participate in the ecosystem rather than Ahlan trying to provide every underlying service itself.

7. You’re building for both individual users and organisations such as employers and schools. How do those different customer groups fit into Ahlan’s long-term vision?

They’re really two sides of the same ecosystem. For an individual, Ahlan should feel like a personalised relocation and settlement companion. For an employer, we’re building dedicated employer profiles and an organisation layer that can support international recruitment, onboarding and settlement.

An employer could showcase its organisation and opportunities, receive job applications through Ahlan, and then support successful international hires through the same platform once they are relocating.

The employee and their family could then use Ahlan for housing, schools, local services, events, community and ongoing guidance. That creates a much more complete journey: discover an opportunity, apply for the job, relocate, find somewhere to live, arrange schooling and settle into the country – all through one connected platform.

For schools and other organisations, there’s a similar logic. They can have a structured presence within the platform, connect with high-intent relocating users and become part of the wider settlement journey. Long term, I think that combination of B2C and B2B2C is central to the model.

8. Looking ahead, what are your ambitions for Ahlan over the next few years, and do you see the platform expanding beyond the UK-Saudi corridor into other international relocation markets?

Absolutely. Saudi Arabia is where we’re starting, and I think it’s the right market in which to prove the model because of the scale of international talent coming into the Kingdom and the pace of transformation taking place. But the problem Ahlan is solving is global.

Every international move involves the same challenge: somebody is leaving one system they understand and entering another one they don’t. Our ambition is for Ahlan to become the trusted operating system for global mobility. The UK-Saudi corridor gives us a focused place to validate the product, partnerships and commercial model. From there, we can expand into other corridors and eventually other markets where international professionals, families, students and organisations face the same fragmented settlement experience.

The goal is for Ahlan to become more than a source of information. It should become the place where people can discover, decide and take action across the entire relocation journey.

The name Ahlan means “welcome”, and that’s ultimately what we want the platform to represent. Wherever somebody is moving, they should be able to move, settle and thrive with confidence.

The post A Chat With Abiel Ghezae, Founder And CEO Of Ahlan, On Building The Operating System For Global Mobility appeared first on 91探花.

External hiring and standard training modules can’t replicate thirty years of tacit, unwritten judgment that simply leaves the business whenever a senior engineer retires, given that the rationale behind those decisions was never recorded in a manual. Compounding the problem, the UK has a severe shortage of technicians with five to fifteen years of experience, leaving no intermediate tier to pass that wisdom down the line.

Hall argues this is precisely where Industrial AI steps in, bridging the gap between operational data and the context behind it. By embedding that reasoning directly into daily workflows, decades of institutional memory become an active operational asset, compressing the learning curve and giving newer workers access to insights that previously took years to build.

Cathie caught up with us to break down how to deploy AI in asset-intensive industries, why the technology is empowering junior staff, and her direct message to leaders sitting on the fence.

AI skills discussions often focus on general digital literacy. What does effective AI adoption and training look like in technical and industrial environments?

Focusing only on general digital literacy risks missing the real opportunity for industrial organisations. Too many businesses approach AI as another piece of software, rather than a capability that can fundamentally change how people work. It’s not about using AI to remove people or reduce entry-level opportunities; it’s about helping workers make better decisions and access the knowledge they need at the point of work.

Industrial environments don’t just need tools that answer generic queries. Industrial AI can help asset-intensive industries surface operational context, access relevant information and improve decision-making in real-world environments. Effective AI training therefore needs to focus on capability, not workforce reduction.

Applied AI training should help workers use AI to access relevant history, previous decisions and operational context within their workflows. By enabling people to interact with complex industrial processes using natural language, organisations can help both experienced employees and newer workers build capability, while keeping human expertise and oversight at the centre.

How exactly does AI capture institutional expertise so younger workers perform at a senior level faster?

It comes down to mapping how unstructured human reasoning influences structured operational data. AI maps the link between informal notes or email exchanges and formal ERP records, then embeds that context into the daily workflow.

When a younger engineer enters the shop floor or field environment, the relevant history, prior decisions and underlying reasoning can be surfaced alongside the task, giving them access to knowledge that would traditionally take years to build.

AI elevates the baseline performance ceiling. Instead of leaving a junior technician to guess or blindly navigate disconnected folders, the system actively surfaces relevant historical choices and prior reasoning pertinent to the job at hand.

When junior workers can direct these complex processes safely through plain language, supported by the organisation’s collective memory, their confidence can grow significantly. Risk is mitigated for the employer, safety is enhanced and the work is performed with the benefit of accumulated organisational knowledge.

Why is AI proving to be a workforce equaliser, rather than a threat, for younger and less experienced workers?

Six in ten young people in the UK鈥檚 NEET cohort have never held a paid job, highlighting the challenge many face when entering the workforce. AI can help lower that barrier by giving newer workers access to the knowledge, context and support they need to succeed.

When an Industrial AI system surfaces the right context and allows a newcomer to interact with complex, multi-layered processes using plain language, it reduces reliance on years of specialised jargon or institutional knowledge built over time. A lack of traditional experience doesn’t have to become a barrier to contributing effectively. AI can help newer workers build confidence and capability, while keeping human expertise and judgement at the centre.

What impact are organisations seeing from using AI to expand workforce capacity?

Organisations are increasingly using AI to expand workforce capacity by helping employees spend less time reacting to problems and more time focused on higher-value work. The biggest opportunity isn’t replacing people, but enabling existing teams to work more effectively by giving them faster access to the information, insights and expertise they need.

We’re seeing this play out across industrial environments. For example, William Grant & Sons is using AI-driven predictive maintenance capabilities to combine live sensor data with historic asset information, helping engineers identify potential issues earlier and reduce disruption. At its Girvan site, this approach is expected to deliver 拢8.4 million in annual savings through improved maintenance, reduced downtime and increased operational efficiency.

This demonstrates how AI can support skilled workers by reducing operational friction, allowing engineers to focus on tasks that require experience, judgement and problem-solving.

To finish, what is the single piece of advice you would give to industrial leaders who are currently sitting on the fence about deploying Industrial AI?

Stop viewing Industrial AI as a future technology trial and recognise it as an immediate operational priority. The organisations that benefit most will be those that use AI not only to automate tasks, but to make expertise more accessible across the workforce. By combining the knowledge of experienced employees with the capabilities of the next generation, businesses can accelerate learning, strengthen capability and build a more resilient workforce for the future.

Addressing the skills gap requires a different approach to workforce development. By putting the expertise of experienced employees into the hands of those building their careers, Industrial AI can help accelerate learning, strengthen capability and create a more resilient workforce for the future.

The post A Chat With Cathie Hall, Chief Customer And Product Officer At IFS, On How AI Can Preserve Institutional Knowledge appeared first on 91探花.

A Fellow of both the National Institute of Marketing of Nigeria and the Institute of Management Consultants Nigeria, a Certified Management Consultant and a member of the International Council of Management Consulting Institutes, he now directs commercial strategy for sub-Saharan Africa’s largest chemical distribution network. In this position, he manages a portfolio that exceeds 500 product lines across the polyurethane foam, paint, pharmaceutical, detergent and construction sectors.

His track record speaks for itself. Product basket expansion under his leadership has delivered 60% revenue growth, with one division growing its gross profit margin from 5% to a steady 14% over five years, lifting annual sales from $6 million to $25 million. He opened three new branches in Sokoto, Kaduna and Port Harcourt, expanding the company’s Pan-Nigerian footprint by 40% and strengthening its cross-border sales activity. He’s also built an employee appreciation and recognition scheme credited with increasing productivity and cutting staff turnover across the sales team.

We chatted with him to find out more about the SaaS opportunities being missed, what he’s looking for as a judge and his advice for founders entering the competition this year.

You鈥檝e spent thirty years in Nigerian and West African markets across manufacturing, distribution and sales. What does your experience tell you about the SaaS opportunities that are still being missed?

Many African SMEs still rely heavily on traditional sales methods like referrals, physical markets, customer service and word-of-mouth.

As a sales professional building a network and business across the West African market, I’ve found that there’s a severe lack of practical, accessible frameworks that bridge the gap between automation and the day-to-day sales execution for practitioners in developing economies like ours.

In the current fast-moving global technology and business ecosystem, I’ve come to realise that the ability to integrate technology into sales processes effectively is no longer an advantage 鈥� it’s become a necessity for business survival. I’ve found that digital adoption across regional sales operations remains noticeably slow, leaving a clear operational gap that software as a service is uniquely positioned to fill. This imbalance creates a compelling market opportunity for SaaS providers, making immediate investment in modern digital sales infrastructure essential.

You were the first Black director in Nagode Industries鈥� 40-year history. What does that mean to you, and what does it say about the pace of change in African business leadership?

Becoming the first Black director at Nagode Industries represents far more than personal advancement or recognition for decades of sustained performance. It reflects a profound organisation-wide trust that carries genuine responsibility across our 40-year history. This milestone reinforces the fundamental truth that sustained excellence, integrity and absolute commitment can break down traditional corporate barriers.

On an organisational level, my promotion reflects both the progress we have recorded and the positive change we have embraced over the years, reinforcing our commitment to live up to our slogan, “Nagode… Inspiring Africa.” At the same time, it reflects the gradual but important shift taking place across African businesses, where organisations are beginning to recognise the value of diverse leadership perspectives.

As the African economy continues to grow and integrate into the global marketplace, companies are increasingly realising that inclusive leadership strengthens innovation, decision-making and long-term business performance. I look forward to seeing diverse leadership become the norm and not the exception across the African corporate landscape.

You鈥檝e written a book on AI for salespeople. How do you think AI is changing B2B sales specifically, and what should SaaS founders building in this space understand?

As I enumerated in my book, The Salesperson鈥檚 Pocket Guide to Artificial Intelligence, AI is already transforming B2B sales efforts across several core areas. It automates repetitive tasks such as email drafting, report generation and personalised product recommendations. It leverages predictive analytics to determine future sales outcomes and identify customer behaviour patterns. Additionally, it streamlines competitor analysis and powers automated customer service operations.

In the evolving digital era where AI is redefining B2B sales, it’s important for businesses to recognise that technology is simultaneously changing how buyers buy and how sellers sell. This serves as a clear pointer for SaaS founders building in this space to focus their efforts on leveraging these core shifts across the B2B sales landscape.

For instance, as buyers seek comprehensive product details before ever speaking to a salesperson, your website, content, product documentation, customer evidence and related assets must be AI-discoverable and self-service friendly. Similarly, as personalisation becomes the expectation, your go-to-market strategy must leverage customer-specific insights, as generic messaging will simply fall short of its objectives.

What are you looking for when you evaluate a SaaS company entering this competition?

Experience has shown that most inventors do not struggle with the process stages of invention from ideation and evaluation to prototyping, testing and implementation. Instead, they struggle with leverage.

My assessment of a SaaS startup in this competition will be based on how it intends to leverage these efforts. What’s the most expensive problem the software is trying to fix? Is the content original and creative? How scalable is the innovation? What’s the marketability of the product? How user-friendly is the product? What depth of impact will it create in the business, marketplace, industry or economy?

What do you think makes a SaaS product genuinely defensible in an emerging market context, where distribution and trust are often harder to build than the technology itself?

In our organisation, sometime in 2024, we onboarded to a new accounting software package, but the project suffered a setback owing to a number of clear reasons. I believe a combination of specific factors is what really makes a SaaS product defensible.

Distribution and trust are rarely built quickly around a newly introduced innovation. However, these challenges can be overcome once a SaaS company convincingly addresses initial friction regarding product cost, service availability, potential loss of man-hours, fear of product failure, data insecurity and unreliability.

Other complementary factors that render a product defensible include localised workflow knowledge and deeply embedded customer relationships.

What is the biggest mistake you see early-stage SaaS founders make when trying to enter markets like Nigeria or West Africa?

Major mistakes SaaS startups make when introducing their products to emerging markets like Nigeria or West Africa are quite common.

The first is the temptation to consider the country or region a digitally developed market rather than a developing one. Another is placing attention on the technology instead of prioritising the problem the product addresses in the region. Startups also fall into underestimating trust-building, overcomplicating the product and paying little or no attention to local workflows. Finally, they often assume self-service growth rather than investing in initial customer engagement, relationship building, customer education, hands-on onboarding and other similar efforts.

What does success look like for the SaaS sector over the next five years?

In five years, success for the SaaS sector in would mean progressing from product penetration effort and promise to reliability, resilience and sustainability. This will happen through building trusted, profitable, AI-enabled companies that are deeply embedded in how businesses operate, while creating scalable solutions that can compete both regionally and globally.

What is your number one piece of advice for entrepreneurs entering the competition this year?

The most successful inventor isn’t the one with the most sophisticated technology, but one who deeply understands a real customer pain point and solves it better than anyone else.

Against this backdrop, therefore, my number one piece of advice for entrepreneurs in the competition this year is to fall in love with the problem, not the solution. Before scaling, make sure you can clearly answer: What is the most expensive problem we are solving and why are customers willing to pay us to solve it?

The post A Chat With Dr Kayode Adedapo Kolawole, Sales Director At Nagode Industries And SaaS 66 Judge appeared first on 91探花.

Today, frendo is building the data, support and care infrastructure for endometriosis and complex chronic pain.

Its free app helps people track symptoms, understand patterns, measure changes in their quality of life and communicate their experience more clearly. frendo@work helps employers better support people living with endometriosis and chronic conditions. frendo Connect is building a trusted network of clinicians and specialists to help people find appropriate care. And frendo Intelligence uses structured, longitudinal patient-reported data to contribute to the research and evidence base that endometriosis has historically lacked.

Together, these tools are creating a more continuous connection between patients, clinicians, researchers, employers and healthcare systems.

1. What prompted you to make frendo completely free, and why did now feel like the right time to remove the subscription fee?

The honest answer isn’t that frendo has suddenly become a unicorn and no longer needs revenue. frendo is a commercial business, not a charity, and it must have a sustainable model to continue growing and supporting people.

But every commercial decision must ultimately come back to what patients need, and this was my wish from the start. frendo was built from my lived experience and has since been shaped by the thousands of lived experiences shared with us. We know how much people with endo already pay, through private appointments, medication, treatments, lost income and years spent fighting to access appropriate care. Digital real-time support shouldn’t become another cost.

Our commercial model is increasingly focused on creating value through credible partnerships with employers, healthcare systems, researchers and other organisations, rather than placing the cost on the individual patient. Making frendo free allows us to remain true to why it was created while building a more scalable and sustainable business around it.

2. You鈥檝e spoken about the financial, professional and personal costs of endometriosis. How much of a barrier do you think the cost of healthcare and support still is for people living with the condition?

It remains an enormous barrier. The cost isn’t only limited to medical appointments or treatment. It can include medication, travel, childcare, complementary therapies, fertility treatment and mental health support, as well as lost income from taking time off, reducing working hours or having to leave employment altogether.

The consequences extend far beyond healthcare costs. Endometriosis can disrupt education and career progression, affect fertility and family-planning decisions, place significant strain on mental health and relationships and erode someone鈥檚 long-term financial security and quality of life.

Many people feel forced into private care, often at great expense, because they can’t wait indefinitely on waitlists for answers, but that option isn’t available to everyone. It creates a deeply unequal system in which the speed and quality of care someone receives can depend on what they can afford.

Making frendo free won鈥檛 solve those inequalities, but it removes one unnecessary barrier to information, tracking and support.

3. You founded frendo after your own experience of living with endometriosis and struggling to be heard. How has that personal experience continued to shape the platform six years on?

My lived experience gives me the lens through which I lead frendo, but the platform has been shaped by the thousands of people who have shared their experiences with us.

I have lived through almost every stage of the endometriosis journey: the loneliness and confusion of an 18-year wait for answers, diagnosis and multiple surgeries, the fear of being told I would never have children and the reality that life doesn鈥檛 suddenly return to normal after diagnosis. Eventually, my quality of life became so poor that I needed a hysterectomy to mitigate the adenomyosis and endometriosis. During severe flares, I couldn鈥檛 properly care for the young baby that I鈥檇 been so lucky to have, and the choice of whether to try for another child was effectively taken out of our hands. I’m now navigating the impact of endo alongside menopause.

That continuing journey has shaped how frendo has evolved. Diagnosis isn’t the finish line for an endometriosis patient. People need support before diagnosis, through treatment and surgery, and throughout the years that follow. That’s why frendo looks beyond periods or individual pain episodes to the whole person 鈥� their symptoms, quality of life, fertility, mental health, relationships, work and changing needs over time.

4. You鈥檝e expanded frendo beyond period tracking to include ovulation, ovarian pain, bowel and bladder symptoms and quality of life. Why was it important to take this broader approach?

Endometriosis isn’t a 鈥渂ad period鈥� condition, and a period tracker alone can’t represent the experience of living with it.

Pain can occur during ovulation or at any point in the month. Symptoms can involve the bowel, bladder, lower back, legs, digestive system, energy levels, sleep and mental health. Some people don’t menstruate because of hormonal treatment, surgery, menopause or other circumstances, but they can still live with significant symptoms.

Taking this approach allows people to build a more accurate picture of what’s happening across their whole body and life, rather than viewing each symptom in isolation.

5. Endometriosis can affect almost every part of someone鈥檚 life, not just their menstrual cycle. What do you think is still misunderstood about the condition and its wider impact?

The biggest misunderstanding is that endo is confined to menstruation and fertility. Those are important aspects of the condition, but they’re not the whole story.

Endometriosis can affect someone鈥檚 digestive and urinary health, mobility, sleep, mental health, relationships, education and career. Persistent pain can also change the way the nervous system processes pain, meaning the impact may continue even after surgery or hormonal treatment.

We also underestimate the cumulative effect of repeatedly not being believed. When someone spends years being told that severe pain is normal, they can begin to doubt their own body. Endometriosis isn’t only a reproductive health issue; it’s a chronic, whole-person condition with significant social and economic consequences.

6. What can tracking symptoms and quality of life over time actually help someone understand or communicate when they鈥檙e seeking medical care?

Tracking can turn a series of seemingly isolated and invisible incidents into a visible pattern. It may help someone recognise whether pain appears around ovulation, whether bowel or bladder symptoms worsen at particular times, or whether fatigue, sleep and mood change alongside physical symptoms.

It also gives people something more structured to bring into an appointment. Instead of trying to recall months of symptoms under pressure, they can show their frequency, severity and impact over time.

Tracking can’t diagnose endometriosis and should never replace clinical care, but it can help patients describe their experience more clearly, ask better informed questions and advocate for the most appropriate investigation and support.

7. What have you learned from frendo鈥檚 users over the past six years about what people with endometriosis actually need from digital health tools?

We’ve learned that people don’t want to spend their lives recording every detail of being unwell, and they shouldn’t be left to navigate the system or advocate for appropriate care alone. A digital health tool must be simple, flexible and genuinely useful.

People want help understanding what their information means, not just graphs or diaries. They want to prepare for appointments and communicate the impact their symptoms are having on their day-to-day life, without having to start from the beginning every time they encounter a new clinician.

Above all, they want to feel believed. Technology should reduce the burden placed on the patient, rather than creating another task or asking them to continually prove their pain.

8. Your existing subscribers are becoming Lifelong Ambassadors and will receive free access for life. Why was it important to recognise your early users in this way?

Our users, early and current, have always been and will remain the driving force behind frendo. Our early subscribers supported us while the platform was still developing and made it possible for us to reach this point. They were never simply customers; their feedback, trust and lived experiences helped shape what frendo has become.

Making frendo free shouldn’t mean overlooking the people who supported us from the beginning. Our Lifelong Ambassadors will be recognised as founding members of the frendo community and included in the next stage of our growth, with continued access to new patient-facing tools, services and opportunities as frendo evolves.

It’s our way of saying thank you and ensuring they remain part of what we build next.

9. Now that frendo is free, what does the next phase of the business look like, and how do you plan to reach more people living with or investigating endometriosis?

Making frendo free allows us to reach more people, including those who have suspected symptoms of endo and may still be years away from receiving a diagnosis. It also enables us to build a broader, more representative picture of how endometriosis affects people over time.

Our next phase is focused on growing the wider frendo ecosystem. Through frendo@work, we’ll continue helping employers provide better workplace support. Through frendo Connect, we’re building a trusted network that can help people find clinicians and specialists with genuine expertise in endometriosis. At this stage, we’d specifically like to hear from endometriosis-focused clinicians and clinics, as well as other specialists working across endometriosis care, who would like to join our network.

Through frendo Intelligence, our growing global longitudinal dataset can help answer important research questions that snapshots and one-off surveys can’t. By following symptoms, treatment experiences and quality of life over time, we can contribute real-world evidence to the research, service design and clinical innovation that endometriosis has been missing for too long.

The longer-term ambition is to create a continuous data and care layer between patients and the wider system, so that what happens in someone鈥檚 life between appointments is no longer invisible.

10. If you could change one thing about the way endometriosis is diagnosed, understood or treated today, what would it be and why?

I would change where endometriosis sits within healthcare. It’s still treated predominantly as a gynaecological or reproductive condition, when it can affect the whole body and needs multidisciplinary care.

I can’t emphasise this enough: endometriosis doesn’t begin and end with periods or fertility. It’s a chronic inflammatory condition that can involve multiple organs and affect the digestive and urinary systems, nerves, immune function and the way pain is processed. Its impact can continue after surgery, hysterectomy or menopause.

As long as we continue to view it only through a reproductive lens, disease will be missed or left untreated, organs may be damaged, fertility compromised and persistent pain poorly understood. Clinicians also need to keep pace with credible advances in diagnosis and treatment, including specialist ultrasound, improved MRI protocols and validated emerging imaging technologies. Innovation can’t improve diagnosis if it never reaches everyday clinical practice.

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This year鈥檚 Spotlight is the first to combine the brand visibility insights of Adobe and Semrush, following the recent completion of the company acquisition in April 2026. 91探花 spoke with Leigh McKenzie, Director of Online Visibility at Semrush, an Adobe company, to chat all things AI visibility and Spotlight, ahead of the conference.

There Are Plenty Of Marketing Conferences Out There. What Makes Spotlight Different?

Spotlight is our flagship marketing conference, and this year we’re orienting everything around what’s happening with AI search and brand visibility. It’s specifically not an SEO conference; there are other events in our portfolio, and from other companies, aimed squarely at SEO practitioners.

We still believe SEO and search marketing are fundamental, but the scope has been expanding for years now. It’s not just the SEO and content teams doing their own thing; it’s brand, product, PR and customer success all coming together, especially in the age of AI. Spotlight is bringing together senior marketing leaders to learn how to stay visible in the age of AI and win what’s next.

We’re planning more than 100 sessions with around 1,000 marketers, and speakers from the likes of OpenAI, ElevenLabs and Uber, plus agency partners like WPP and Flight Story. The main conference is on 13 October, and we’re also running a pre-event AI Search Bootcamp that gets more into the weeds on how to actually approach AI search, including our framework for building brand visibility in AI search called the AI Operating System. Attendees will get hands on, and hear directly from other Semrush customers.

Why London Specifically, After Amsterdam?

Amsterdam has been a fantastic home for Spotlight over the past two years, and it remains an important hub for us. But Spotlight itself has grown both in the audience it attracts and in the conversations we want to lead.

London felt like the natural next step. It brings together one of the most concentrated communities of global brands, technology companies, agencies and marketing leaders in Europe, at a moment when AI is fundamentally changing how brands are discovered and how marketers think about visibility.

That鈥檚 really what Spotlight is about this year: bringing the industry together to tackle that change. Moving to London gives us the scale and diversity of audience to make that conversation even bigger.

AI Is In Everything Right Now. What Makes It Different For Marketing, And What Do You Most Want To Put The Spotlight On?

We’re talking about how AI search is fundamentally changing how people discover, compare, and choose brands. And at its core, it still comes down to authentic content, and brand authority.

Brand visibility is a collaborative, cross-functional effort, not just owned by the team responsible for publishing content on the website, as the SEO teams of the past were. We want to bring all the different departments together and show them how they fit into this ecosystem, how they can use the new tools and technology, and how to build the organisational awareness and change management needed to do the work.

Our message to marketers is two-fold: Invest in the right product and tools to measure your brand visibility, and create the best possible content to help your brand stand out, across blog posts, LinkedIn, Reddit, video on YouTube 鈥� anywhere you can reach your audience. To win AI visibility with users on LLMs, your third-party content is just as important as your owned properties.

You Run An SEO Team Yourself, So This Is Close To Home – What Has AI Search Fundamentally Changed?

Honestly, I’m more excited to work in this industry as an SEO (or an AEO or GEO, to use the newer terms) than ever before. For people who’ve cared about the technical side of marketing, content and how search engines 鈥� and now AI engines 鈥� work, there’s so much more to learn and figure out, and much more data available to make strategic decisions.

There’s also a much bigger opportunity to influence what other teams are doing by being part of the conversation on brand and paid budgets, knowing what the social team is up to, understanding how customer success handles support tickets, and even getting involved in real conversations on Reddit.

Early on there was a lot of fear; there were dozens of articles claiming “SEO is dead” and we did see AI organic traffic start to decline. But what we haven’t seen is any decline in people seeking to solve problems and consumers buying things they need, and search is critical to that.

So we’re helping companies adapt to a world where success isn’t judged purely on organic traffic and directly attributable marketing channels. The companies thinking bigger and making the right investments in brand visibility now, with the right tools and teams, are the ones that’ll win in the years to come.

Have We Gone Past 鈥淧eak AI鈥� Or Is It Settling Into Where It Realistically Fits?

When it comes to generative AI for content creation, it鈥檚 somewhere in the middle. The people who feel strongly about one side or the other are missing the nuance where the truth actually lies. We want to highlight how to invest in content the right way 鈥� using AI responsibly to create quality, authentic content, but not just producing ten times more just because you can.

It’s about creating more of the right content: the kind that stands the test of time and stays indexed month after month, rather than popping up and then declining. Content that drives views on YouTube, impressions and interactions on social media, and comments on Reddit is worthwhile, because of the impact it has on brand and downstream conversions. When it’s done right, it all comes together and helps businesses grow.

With A Room Full Of People From Both Ends Of That Spectrum, How Do You Avoid It Becoming An AI Echo Chamber – Keeping The Human Input Without Ignoring AI?

It’s something we tackle day to day at Semrush, and I think we’ve struck the balance more successfully in recent months by using AI to do better work, not just more work. When we think about the talks we want to cover at the Spotlight conference, the question is: how are people doing great work for both humans and machines, and how has their workflow changed?

In a lot of cases AI is involved, but we’re not interested in hearing from someone who used ChatGPT to publish 10,000 blog posts and shares what it looks like one month in, because we’d expect that to fall off within three months.

We’d rather showcase the most exciting work in marketing right now. As an example, we’re investing more than ever in affiliate and creator content, partnering with people making content about the real jobs to be done that matter to people in SEO and content marketing. To reach people, you need content that’s actually engaging. Nobody wants to watch an AI read a script with no real substance behind it.

Where Does AI Search Fit Alongside Traditional Google Search?

They’re absolutely tied together, it’s not a pure replacement. I think we’ll continue to see organic traffic to websites decline over time as more activity happens directly within conversational AI, whether that’s Google Gemini, AI Mode, or AI Overviews right there in the SERP – and then ChatGPT, Claude, and Perplexity beyond that.

But we see them as interrelated and expansive at the same time. We’re investing in YouTube, Reddit, and LinkedIn as inputs to search, partly because they rank directly on the results page: you’ll see AI Overviews, then the top three videos, blog posts, and an interesting LinkedIn conversation. All of those pieces matter.

We want to help our audience work out the right mix of investment for their business, and then how to track it and operationalise it internally. Tools like Semrush and Adobe Brand Visibility help marketers and enterprises to measure, track, and improve their website performance and overall brand visibility.

If Traditional SEO Now Feeds AI Search, How Do The Two Affect Each Other?

We start from the view that your website is still your foundation. There’s been talk that the website is no longer relevant, but we believe investing in it as the source of truth for your brand is critical – your homepage, your product and services pages.

We’re still managing hundreds blog posts on the Semrush blog, plus our knowledge base and support articles. And everything we publish, we’re evaluating for SEO: is it technically set up to be crawled and indexed? Is it engaging enough that Google wants to keep it in the index over time? How will it perform in the ChatGPT, Bing, and Brave indexes too?

The expansion is everything beyond that. Previously, most SEO teams generally weren’t thinking about publishing a YouTube video on the same topic as a blog post, or about the reputation-management side, considering how important conversations on Reddit can be, or Tripadvisor for local businesses, as examples.

The fundamentals still matter. You still need a technical SEO team and a technically sound website. But even link building has changed a lot: it’s less about getting a followed link and more about earning contextually relevant brand mentions, whether in text, a video script or a LinkedIn conversation. It’s the same outreach and partnership thinking SEO teams have always done, just with a different goal.

What鈥檚 Your Message To Brands And Businesses That Feel They鈥檝e Fallen Behind And Need To Catch Up?

It’s still early, and there鈥檚 a wide open opportunity for marketing leaders to get in the game. If you’re focused on building a great, well-rounded business, AI search is just one point at the end of the tunnel; it’s also about all the other things you’re doing.

We want to help people work out the right mix of activities and prioritise the work that’ll be most impactful. It’s easy to get caught up in feeling there are a thousand things to do, but for most businesses there are really just a handful of things that, done consistently week after week 鈥� whether your team is one person or a thousand 鈥� pay dividends over time.

Invest in your brand, make sure your owned digital properties are technically sound and the content aligns with your brand message, and work to match your brand promise with your customer experience.

Why Does This Matter At CMO And Board Level?

AI visibility is not a nice-to-have. There is so much opportunity for brands to capture consumer interest on these new search surfaces they鈥檙e using. We recently released a Semrush study that looked at 50,000 brands and found that 85% of topics on ChatGPT still have no clear brand owner. That means they’re up for grabs, and the playing field is wide open.

From a CMO’s perspective, it comes down to integration. What AI search is proving is that the companies telling the same story consistently, day after day, and obsessing over their customers across every channel, are the ones winning. That alignment has to come from the CMO, or even the CEO.

Marketing leaders need to take visibility seriously, because it’s becoming a board-level concern. That鈥檚 why Spotlight is so needed right now.

There鈥檚 so much value for senior marketing leaders, particularly CMOs, to share their experiences with brand visibility and learn from some of the biggest brands, with more than 80 experts on stage talking through their AI visibility strategies: what they’ve tried, what they’ve learned, and what isn’t working so well.

After the initial uncertainty when AI search first arrived, we’re now at a point where there are practical things you can do to build your AI visibility, and attending Spotlight will help teach you how.

Register for .

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Today, Ollie focuses on helping business leaders navigate AI adoption, changing the focus from raw tech to how AI reshapes people, skills and daily operations. He shares his insights on what the UK’s new AI Minister should focus on first, why scaling business adoption beats chasing unicorns and how executives can close the increasing skills gap.

The UK now has its first dedicated AI Minister, Kanishka Narayan. What do you think this appointment signals about the Government’s changing attitude towards AI, and what would you like to see him prioritise first?

“It shows the Government recognises AI is much bigger than a technology conversation.

鈥淭his is a broader conversation about productivity, skills, businesses and the future of work, and my hope is that success will be measured in this holistic way too.

鈥淔rom speaking to employers across the UK, the biggest challenges are rarely about accessing AI tools. They’re about knowing where to start, building the right skills, and creating the right conditions for adoption. That’s where I’d like to see him start.”

You鈥檝e argued that the UK should focus less on simply creating AI companies and more on helping existing businesses adopt AI successfully. Why do you think this distinction matters?

“Too much of the conversation still centres on the technology itself. The bigger opportunity is helping businesses use AI to become more productive, reduce repetitive tasks and give people more time to focus on work that creates greater value.

鈥淎 recruiter finding talent faster, a manufacturer improving quality control or a healthcare worker spending less time on administration might seem like small improvements individually. But collectively, they could have a significant impact on the UK economy.

鈥淚f thousands of organisations each become a little more productive, the impact will be far greater than the success of any single AI business.”

La Fosse’s research suggests that 69% of workers believe their organisation needs a dedicated AI specialist at the most senior level. What does this tell us about the current gap between businesses wanting to adopt AI and actually knowing how to do it?

“Our AI in the Workforce research found that 69% of workers believe their organisation needs a dedicated AI specialist at the most senior level, while 80% of existing C-suite leaders agree there is a need for this expertise.

鈥淭hat tells you businesses are recognising the importance of AI leadership, but many are still working out what that should look like in practice. Investment in people should be treated with the same importance as investment in AI. The hardest questions here aren’t technical, they’re about people. Which skills will matter most, how roles will change and how leaders help employees use AI with confidence 鈥� these are the challenges businesses need help navigating.”

There鈥檚 a lot of discussion around AI potentially replacing jobs, but you put considerable emphasis on workforce capability and skills. What skills do you think UK workers and business leaders most urgently need to develop?

“The organisations that succeed will be those that build AI capability across the business, from leadership teams through to employees using these tools every day.

鈥淪kills-wise, that means leaders who understand AI well enough to make good decisions about where it fits, and employees who have the confidence and practical know-how to use it in their day-to-day roles. It’s less about everyone becoming a technologist, and more about building judgement and the ability to know when AI helps and when it doesn’t.”

Do you think smaller businesses and startups are currently at risk of being left behind in the AI race, particularly when larger companies have greater access to funding, talent and technology?

鈥淭here鈥檚 a real risk that AI adoption becomes something only larger businesses with significant technology budgets can do properly.

鈥淪maller organisations make up a huge part of the UK economy, so it matters enormously that they鈥檙e not left on the sidelines. The opportunity is to give them the confidence, skills and practical support to start small, prove where AI creates value, and scale from there.鈥�

What could the Government realistically do to make AI adoption more accessible to smaller businesses, rather than simply producing another strategy or set of guidelines?

鈥淚鈥檇 focus on practical incentives that reduce the cost and risk of adoption. That could include stronger tax incentives for SMEs investing in AI, technology and R&D, helping businesses offset some of the upfront cost of adopting new tools and building new capabilities.

鈥淎longside that, Government could provide targeted support for AI skills and training, and make it easier for smaller businesses to access expertise and funding to experiment with AI.

鈥淭he US has been very effective at using incentives to encourage technology investment. The UK should be equally ambitious. Rather than another strategy document, we should be making it financially easier for businesses to invest, experiment and build the skills they need to turn AI into productivity.鈥�

Your research found that 73% of C-suite executives have uploaded confidential company data into AI tools, while 78% have used AI for work they are not trained to do. How concerned should businesses be about this, and what does responsible AI adoption actually look like in practice?

“Those numbers should concern every leadership team. Our research found that 73% of C-suite executives have uploaded confidential company data into AI tools, while 78% have used AI for work they are not trained to do.

鈥淭hat highlights exactly why organisations need strong leadership and the right skills in place as AI becomes part of everyday working life. Responsible adoption in practice means clear guidance on what can and can’t go into these tools, proper training so people understand the limits of what they’re using, and leadership that treats governance as seriously as it treats the technology itself.”

You鈥檝e said that the Government should lead by example when it comes to AI adoption. What are the areas of public services where you think AI could make the biggest difference, and where should we be more cautious?

鈥淭he public sector has a huge opportunity to use AI to reduce administration and give people more time to focus on the work where human judgement matters most, whether that鈥檚 frontline care, casework or complex decision-making.

鈥淲here I鈥檇 urge caution is when AI moves from supporting judgement to replacing it, particularly in services dealing with vulnerable people. Leadership, governance and clear accountability will be just as important as the technology itself.鈥�

If we look five years ahead, what would convince you that the UK’s AI strategy has actually worked? What would need to have changed for businesses, workers and the wider economy?

“Britain does’t need to create every AI breakthrough to benefit from this technology.

鈥淲e have a real opportunity to become one of the best places in the world for organisations to adopt AI successfully and turn new technology into long-term economic growth.

鈥淚f, five years from now, businesses are more productive, employees feel better equipped for the future, and public services are working better because of AI, that will be the measure of success.”

The post A Chat With Ollie Whiting, CEO Of La Fosse, On The Human Side Of Digital Change appeared first on 91探花.

Starling Memory Works is where those skills converge. The company started with what were, effectively, operating manuals for AI systems, graduated to an AI-agnostic knowledge repository and ultimately became an “Org Brain” constructed from those twenty-five years of business blueprints. The platform gives organisations a permanent, governed memory that any AI can work from 鈥� so the AI finally knows the business, and the business owns what it knows.

Kincade first debuted the Hierarchy of Organisational Values at a January 2023 summit co-hosted with Ari Meisel, spending the next two years refining it with clients before adapting it for AI. He wrote Starling’s operating system himself, in English rather than code, before bringing in an engineering team to build it into a platform. That team included CTO Jeremy Decker, who previously designed a back-end for Mastercard, divisional leaders Zuhayr Tariq, Ahmed Khalid and Andrey Gubanov, and Harol Garcia, who joined in June to build the company’s own repository.

He shared his thoughts with us on why he thinks most AI tools have the ownership problem backwards.

What problem were you trying to solve, and why a new approach rather than an improvement on existing tools?

Every AI tool on the market shares one assumption: the intelligence lives on the machine’s side, accumulating inside a platform you don鈥檛 own.

The fix is organisational, not technical. We have to decouple the AI system from our memory, which includes daily work (i.e., active memory). Whatever the model needs to provide contextualised assistance has to live in a governed, plain-text repository the organisation owns. Any 鈥榩ermissioned鈥� AI can read and write to it, but the repository has to be so well-wired that retention is not even necessary.

That’s why it had to be a new approach. The industry connects AI to knowledge through derived copies – embeddings, vector databases, retrieval pipelines – shadows of the truth that start drifting the moment the truth changes. We eliminated the category. In Starling, the library itself is the cache. Context is assembled fresh from your canonical source every session. Read, reason and forget – the next session reads the same source again. Nothing goes stale, because there is no copy to drift against. There is only the source of truth.

You’ve described most AI leaders as having an Oppenheimer complex. What do you mean, and how does Starling differ?

This summer, a thousand AI workers, including prominent influencers, petitioned Washington to regulate their own field. When the people building a technology ask the government to restrain them, they’re admitting they haven’t built restraint into the technology itself.

I’d rather keep the machines on our side through architecture and design – which means, in practice, that people hold every important switch. Nothing the AI writes becomes company truth until a person approves it. Every answer shows where it came from and who verified it. A written code of conduct governs what the AI may and may not do.

The AI can do the drafting and the finding; only people do the deciding. That’s what putting humans at the centre actually entails. It鈥檚 not a policy statement, but switches only people can flip.

Why make Universal Cognitive Architecture free, and what do you hope it enables beyond Starling?

Governance shouldn鈥檛 be proprietary, nor should the ability to own your memory. The standards that changed the world were open: the Dewey Decimal System didn’t license libraries; HTML didn鈥檛 paywall the web; and Git didn’t meter commits. UCA (Universal Cognitive Architecture) gives every piece of organisational knowledge a permanent, human-readable address, and that only becomes infrastructure if anyone can build on it without asking me for permission.

UCA is a free standard with instructions on how to wire it into a Claude project. I hope it enables a new profession – Cognitive Designers, able to structure organisational memory for human governance. The first builders shipped their own systems on the published framework before we’d launched anything commercial 鈥� that’s part of the point. If UCA only ever powered Starling, we’d have a killer app. Our ambition is a retrieval and assembly standard people adopt because it鈥檚 fast and effective, not just sovereign.

In short, we want to launch a movement. Honestly, if you follow the logic all the way through, we鈥檙e pursuing an alternative to AI having instant access to all human knowledge. That鈥檚 what the massive data centres are needed for. The DLM solves the big compute question on an organisational basis. With it, companies find their knowledge the same way whether they have 28 documents, or 28,000 – by address, not search.

Data centres are needed to synthesise across knowledge bases built on a SaaS workflow, with scores of document, image and database types, hundreds of APIs and thousands of applications. UCA introduces an AI-native workflow. Knowledge lives in lossless markdown. What leaves the building gets converted when you need it.

You describe knowledge stored inside AI platforms as an operational risk. What does that mean in practice?

Well, first and foremost, when AI trains on your ‘special sauce’, your unique values and protocols become part of the new baseline. Yes, you can write 鈥榥o training and storage鈥� into a Service Level Agreement, but without memory, the AI is a brilliant mess.

Two events this summer showcased the risks of depending on AI platforms. In June, a government directive pulled frontier models from global access overnight. In the 18 days it took to restore access, any working knowledge inside the platform was unreachable. In a separate incident, a security team in the middle of a crisis asked a commercial model for help and was refused by the model鈥檚 own guardrails.

The first is a memory risk: knowledge you don’t hold can be held from you. The second is a cognition risk: rented intelligence can decline you. A Domain Language Model survives both. We define a DLM as stateless, session-based, and redundant AI systems reading and writing to a sovereign repository. If any one AI system is unavailable, the system can switch to another.

The post A Chat With Chris Kincade, Founder Of Starling Memory Works, On Why Your AI Doesn’t Know Your Business appeared first on 91探花.

I鈥檓 Mark Boost, CEO and co-founder of Civo 鈥� a Sovereign Cloud and AI platform. I鈥檝e spent my career in tech pushing for a cloud industry that’s actually open, fair, and transparent 鈥� which is also why I was a founding executive committee member of the Open Cloud Coalition.

We built Civo to challenge the traditional cloud model and put control back in the hands of users; we wanted to give developers and businesses a real alternative. Simply put, Civo is designed to give you the speed and flexibility of the public cloud, but with the data control, privacy, and honest pricing you鈥檇 expect from private infrastructure.

What defines true data sovereignty, and how can nations avoid losing digital control?

Sovereignty is about jurisdictional control, rather than where a data centre is based. For example, even if your data is stored in the UK, if it’s held by a US provider, it can be accessed by US authorities under the US CLOUD Act. This means it’s never truly sovereign. While open source doesn鈥檛 implicitly deliver sovereignty on its own, adhering to open standards and open architectures can help with this. It can ensure nations don’t rely on entirely locked-down proprietary systems with zero portability or interoperability. The UK can’t deliver meaningful sovereign action without treating open source as a strategic national asset.

That鈥檚 because, on top of jurisdictional overreach and black-box stacks, these closed-loop environments also entrench platform lock-in. Moving to another provider becomes technically difficult and prohibitively expensive, thereby reducing digital autonomy. Without the ability to move, you are effectively ceding long-term control to a foreign nation.

Why is relying on US hyperscalers a mistake for the UK鈥檚 AI ambitions?

Three foreign-owned hyperscalers 鈥� AWS, Microsoft, and Google 鈥� control up to 90% of the UK cloud market. If the UK is to be an AI leader, it must shift from a reactive to a proactive position. In addition to purchasing a balanced portfolio of cloud services, the government must strategically invest in a robust, UK-based ecosystem for data, cloud and AI resources. This will ensure domestic retention of critical computing resources while benefiting the British technology ecosystem through the availability of domestically produced, regulated computing power.

Building our domestic innovation on the backs of the Big Three US hyperscalers takes high-skilled jobs and intellectual property out of the UK. Treating compute and data as a strategic asset, much like our national grid, would create a framework of co-investment and R&D incentives, establishing innovative businesses that can withstand geopolitical headwinds.

How might sovereignty-driven cloud models shape the future of digital infrastructure, particularly in highly regulated industries?

Sovereignty-driven cloud models will shift digital infrastructure away from a single-cloud mindset. Organisations in highly regulated industries will no longer default to just one large provider. Instead, they will adopt a more deliberate approach, where each workload runs based on sensitivity, jurisdiction and risk.

This will drive demand for environments that offer continuity across sovereign, private and public clouds. These systems must allow workloads to move easily as requirements change.
Infrastructure will continue to become more policy-aware. Data residency, regulation and geopolitical risk will now actively shape how systems are designed.

This shift will accelerate the move towards sovereign and locally controlled infrastructure. As a result, organisations will reduce their over-reliance on a small number of global providers. Hyperscalers will remain part of the mix but will no longer be the only option.

AI is amplifying these trends. As organisations deploy more data-sensitive and compute-intensive workloads, control, location and governance become central concerns.

This will force organisations to strongly consider where their AI runs and evaluate the sovereignty-tax trade-offs, balancing the immediate cost efficiencies of the public cloud against the long-term strategic necessity of data ownership and regulatory resilience.

The post A Chat With Mark Boost, CEO And Co-founder Of Civo, On Data Sovereignty And The Case For A UK-First Cloud Strategy appeared first on 91探花.

Before launching , I ran my own construction business. It was a good size; we ran a large team across multiple job sites, and the work was really rewarding. We got a lot done. But tool theft was relentless. It happened on site, from vans, and from lockups. And the financial impact was huge. People often think it鈥檚 kind of a victimless crime because you can always claim on your insurance, but it鈥檚 often not that easy. And when you lose enough and make claims enough, your premiums become so high that it stops being viable. Kynekt is my solution to that.

Designed specifically for trade professionals, it doesn鈥檛 just provide proof of ownership for insurance claims, but unique ID codes for tools, and trackers that can be used by police for retrieval. The aim is to provide everything tradespeople need to protect their assets in one place.

How big is the tool theft problem?

There was a Simply Business survey a few years ago, showing that 78% of tradespeople have experienced tool theft. And that comes at a cost of around 拢100m a year. That鈥檚 a massive impact for any industry. But it鈥檚 not just the financial impact that鈥檚 a concern. Because around half of thefts happen overnight from vehicles, contractors feel personally violated by the experience, and around two-thirds worry about it constantly. While the obvious answer is not to leave your tools in your van overnight, most contractors don鈥檛 have anywhere else to leave them. And our research shows that 68% of tradies worry about this daily.

Why do so many insurance claims for stolen tools fail?

The biggest problem is that 83% of affected tradespeople have no proof of ownership when theft happens, so claims are rejected before they鈥檙e even assessed. And that鈥檚 part of the inspiration for Kynekt. We want to help more people to receive the insurance cover they鈥檙e paying for. Too many tradespeople rely on out-of-date asset records, because keeping up with admin just isn鈥檛 a priority when you鈥檝e got multiple jobs coming in. With Kynekt, you have a tamper-proof, timestamped documentation register as proof. We work with specialist insurer Superscript, who recognise Kynekt as a form of proof of ownership, and will process claims from Kynekt customers making the process straightforward.

What does Kynekt actually do when tools are stolen?

We offer a range of connected services. So, the foundation is a digital ownership register when signing up, which can help with insurance claims. The process is easy – a rapid 2-minute inventory registration via photo scanning, and specialist trade insurers (like Superscript) are already recognising us as a trusted source. Then we offer covert GPS tracking with remote disable, so if tools are stolen, they can be disabled and retrieved – so far we鈥檝e had a 94% recovery rate, with an average of two hours from theft to recovery, versus the 5% recovery rate of tools without tracking. On top of that, we provide a verified second-hand marketplace in the same app, so if you need to sell or buy tools, you can do so with confidence.

Stolen tools often end up on Facebook Marketplace and eBay. Can that pipeline be broken?

Only when verifiable alternatives are available. And that鈥檚 what we鈥檙e trying to offer. Manufacturers don’t build in recovery or take theft seriously – probably because theft usually results in another sale. So, the industry needs a verified marketplace that gives buyers a clean alternative where ownership is proven. If we can make buying from platforms like Kynekt the norm, it will become natural to be suspicious of other online marketplace sales.

What’s the cost of tool theft beyond the kit itself?

There鈥檚 obviously the value of the kit, and the bumped-up insurance premiums. But then you鈥檝e got the burden of missed jobs, lost deposits, damaged client trust, and the reputational hit of not turning up. And that can鈥檛 be underestimated, as most tradespeople work from reputation alone.

While large construction businesses like mine still feel the impact, the hardest hit will always be the sole traders. When tools are stolen from an independent business, it can be devastating. They can lose weeks or even months of work. And that鈥檚 a huge financial and mental burden to carry. Mental health isn鈥檛 something that often gets discussed in this trade, but the Tradespeople Against Tool Theft white paper showed that having tools stolen has had a 鈥渟trong impact” on the mental health of 39% of people involved in the research. And it鈥檚 not surprising to anyone who鈥檚 been unfortunate enough to experience it.

What can we see from Kynekt in the future?

We鈥檝e already made great strides, Kynekt is backed by the police, specialist insurers, and thousands of UK tradespeople. Our aim is to make tool theft unviable. If people won鈥檛 buy the tools you鈥檝e stolen, and the police are able to track and retrieve stolen goods within hours, then there鈥檚 no value in the exercise. Especially if you can鈥檛 even use the tools when you鈥檝e got them because they鈥檝e been remotely disabled. Our next focus will be on growing ToolTrade庐, our verified tool marketplace. Every business has kit sitting idle. ToolTrade庐 lets you sell what you no longer need for real money, buy trusted second-hand equipment, and purchase new from approved vendors – all in one place.

The post An Interview With James Murdoch, Director Of Kynekt, The UK’s Leading Equipment Protection Platform For The Construction And Trades Industry appeared first on 91探花.