The round was led by Heartcore Capital and Balderton Capital, with participation from Evantic, Yellow VC and Entrepreneurs First, alongside a group of angel investors that includes members of the SpaceMaker founding team and operators from companies such as Meta, Hugging Face and Supabase.

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Rethinking a Slow-Moving Industry

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Despite being one of the largest global asset classes, real estate development has remained relatively untouched by modern software innovation. Early-stage processes such as feasibility studies, site analysis and architectural design are still heavily manual, fragmented and time-intensive.

Davis is positioning itself as part of a broader shift away from traditional SaaS tools towards AI-native services that deliver outcomes directly. Rather than offering software to assist architects and developers, the company generates feasibility studies and architectural designs itself, and��then validates them with human experts before delivery.

The goal is simple: reduce the time it takes to move from site analysis to a workable concept from months to just a few days.

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From Tools to Outcomes

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Founded by Mehdi Rais and Amine Chraibi, Davis combines generative AI with architectural expertise to streamline early-stage development. The platform ingests regulatory, technical and market data, turning these inputs into constraints that guide design generation.

Outputs include feasibility studies, volumetric models, floor plans and space planning – all reviewed by human architects before being handed off to developers and investors.

This hybrid model reflects a growing trend across enterprise AI, where companies are moving beyond productivity tools and towards fully integrated, outcome-driven services.

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Davis Introduces Gaudi-1

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Alongside the funding, Davis has also launched Gaudi-1, its first proprietary model designed specifically for architectural generation under real-world constraints.

Unlike traditional generative models that operate in pixel-based environments, Gaudi-1 works in a structured, discrete space. It generates buildings as compositions of architectural elements such as rooms, walls and layouts, allowing for greater control and more reliable outputs.

This approach is designed to better reflect the realities of construction, where regulatory requirements, financial viability and spatial constraints all play a role in shaping design decisions.

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A Growing AI Category

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Davis is part of a broader movement applying AI to physical-world industries, often referred to as “Physical AI.” Similar to how AI is reshaping software development and customer service, startups are now targeting sectors like construction, manufacturing and logistics.

What makes real estate particularly attractive is the combination of high-value decisions and slow-moving processes. Even small efficiency gains can have significant financial impact, especially in early-stage development where time directly affects returns.

Investors are taking notice. According to Heartcore Capital partner Max Niederhofer, Davis stands out for combining three key elements: a proprietary generative model, human validation and a clear impact on timelines in a time-sensitive industry.

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Early Traction and Expansion Plans

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The company is already working with developers across multiple geographies and asset classes, with plans to support hundreds of projects over the next year.

Its technology is designed to adapt to local regulations, allowing it to scale across different markets without requiring entirely new systems for each region.

This flexibility could prove critical as AI adoption in real estate accelerates globally, particularly in markets facing housing shortages or increased development pressure.

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The Bigger Shift in PropTech

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Davis’ approach also signals a broader shift in proptech. For years, innovation in the sector has focused on digitisation – moving processes online or improving collaboration tools. Now, the focus is shifting towards automation and intelligence.

By delivering completed outputs rather than tools, companies like Davis are effectively repositioning themselves within the value chain, sitting closer to decision-making rather than just enabling it.

This raises interesting questions about the future role of architects, planners and developers. While human expertise remains central (particularly in validation and oversight) the balance between manual work and automated generation is clearly evolving.

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The Future for Davis and Gaudi-1

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With fresh funding in place, Davis plans to expand its research capabilities, grow its team and continue developing its AI models.

For co-founder and CEO Mehdi Rais, the ambition goes beyond speeding up workflows. “Real estate is one of the world’s largest asset classes, yet some of its most important workflows still move at a pace that no longer makes sense,” he said. “We started Davis to set a new time standard for real estate development.”

If the company succeeds, it won’t just make development faster – it could fundamentally change how cities are designed and built.

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The startup is positioning itself within an emerging category it calls Physical Observability��– software designed to turn existing industrial camera infrastructure into real-time operational intelligence for sectors such as mining, energy and logistics.

Rather than deploying new hardware, Misti AI’s approach focuses on converting passive video systems into structured, machine-readable data that can support monitoring, safety compliance and operational decision-making.

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Turning Industrial Cameras Into Real-Time Intelligence Systems

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Across heavy industry, millions of cameras are already deployed across sites such as mines, refineries and remote infrastructure networks. However, most of this footage is still used for passive monitoring or post-incident review rather than real-time insight.

Misti AI is aiming to change that by building a reasoning layer on top of existing systems, effectively transforming video feeds into continuous operational data streams.

The company has compared the model to observability platforms in software infrastructure, such as Datadog, but applied to the physical world.

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Early Deployments In Remote Industrial Environments

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The funding announcement comes as Misti AI begins initial deployments across mining and energy operations in Latin America, including sites in Peru.

These environments are often characterised by low connectivity and high operational risk, making real-time monitoring and compliance particularly challenging.

According to the company, early use cases include real-time monitoring in low-connectivity regions, automated safety and compliance workflows, and converting legacy camera systems into actionable operational data.

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Edge AI and Vision-Language Models At the Core

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Misti AI’s technical approach combines edge computing with vision-language models (VLMs), enabling systems to process data locally on-site rather than relying entirely on cloud infrastructure.

This is particularly important in remote industrial settings where connectivity can be limited or unstable.

The company says its focus is not just on detecting events, but on enabling systems to understand context – moving from what is happening to why it matters operationally.

Misti AI is also part of the NVIDIA Inception Program, which supports startups building AI infrastructure and applications.

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A New Category Forming Around “Physical Observability”

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The broader positioning reflects a growing trend in enterprise AI: the extension of software intelligence into physical environments.

While much of the has focused on digital workflows, a new wave of startups is now targeting real-world infrastructure – from manufacturing and logistics to energy and construction.

In this context, Misti AI is betting that existing industrial camera networks represent an underutilised data layer that can be .

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Investor Appetite for Industrial AI Infrastructure Grows

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Fuel Ventures led the round, with founder Mark Pearson highlighting the scale of opportunity in industrial video infrastructure.

He noted that large-scale camera networks in heavy industry remain one of the last untapped sources of real-time operational data, positioning Misti AI as part of a broader shift toward AI-driven industrial systems.

The backing also reflects continued investor interest in deep tech applications of AI, particularly in sectors where automation, safety and operational efficiency intersect.

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Building for the “Physical AI” Era

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Misti AI’s founders describe the long-term ambition as building a foundational intelligence layer for physical operations globally.

While the company is currently focused on observability and monitoring use cases, the broader vision reflects an : systems that do not just analyse digital data, but interpret and act on real-world environments.

As AI moves further into industrial settings, the distinction between software intelligence and physical infrastructure is beginning to blur, and companies like Misti AI are positioning themselves directly at that intersection.

The pre-seed round remains open as the company continues to scale early deployments and expand its presence in industrial markets.

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The California-based company provides a platform that lets developers build, deploy and manage and complex workflows in production environments. Its underlying open-source technology, Conductor, was originally built at Netflix to support its global scale, and continues to power Netflix today.

Orkes has spent four years extending that foundation to AI and agentic systems, building out the orchestration layer that sits between a company’s AI models and its production infrastructure.

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From Pilot To Production

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The funding comes at a moment when enterprise AI adoption is running into a brick wall.

Gartner projects spending will reach $450 billion in 2026, but according to McKinsey, two-thirds of companies were still running AI in pilot mode as recently as 2025. The divide separating proof of concept and production deployment has become one of the most pressing problems in enterprise AI, and Orkes is positioning its platform directly in that space.

Since its $20 million Series A in 2024, Orkes has tripled its customer base and built a developer community with millions of installs. Customers include United Wholesale Mortgage, Quest Diagnostics, Twilio, LinkedIn and Naveo Commerce, alongside developers at organisations including Netflix, JP Morgan Chase, Atlassian, Tesla, Oracle, American Express and GE Healthcare who continue to rely on the open-source Conductor project.

“Orkes gives developers the confidence to deploy AI in production with the reliability, control and scale they expect, and global enterprises rely on the platform for mission-critical operations,” said Alex Scherbakovsky, General Partner at AVP, who is joining the Orkes board.

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What The Platform Does

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Orkes’ platform allows developers to orchestrate complex workflows, build AI agents and run mission-critical applications with the governance and observability required for production environments. Its current suite includes an Agent Runtime for blending structured processes with AI-driven decisions, an MCP Gateway for turning internal APIs into tools that agents can use, and a capability that converts natural language into deployable workflow drafts.

Naveo Commerce, an end-to-end commerce platform, uses Orkes to power dynamic fulfilment and adaptive orchestration across its global supply chain, with AI agents autonomously monitoring inventory, detecting disruptions and resolving issues in real time.

“Commerce is entering a new era,” said Jamie Goldring, CEO of Naveo Commerce. “Agentic orchestration is not incremental innovation but a structural leap forward, enabling enterprises to adapt in real time, unlock new revenue models and achieve resilience at scale.”

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Where The Investment Goes

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Jeu George, co-founder and CEO of Orkes, said the platform is bridging a gap that has held back enterprise AI adoption: “Developers need orchestration, controls and visibility to run advanced AI and agentic systems with confidence. The trust we’re seeing from both the developer community and global enterprises reinforces the role Orkes plays as the missing orchestration layer that makes AI highly reliable, observable and governable.”

Abhishek Shukla, Managing Director at Prosperity7 Ventures, framed the investment as a bet on the infrastructure layer of enterprise AI: “Orkes’ platform gives enterprises a single, governed engine to coordinate large language models, tools, microservices and human review, so AI can safely sit in the middle of mission-critical workflows.”

Orkes was co-founded by Jeu George (CEO), Viren Baraiya (CTO) and Dilip Lukose (CPO), all of whom previously led engineering at Netflix. The fresh capital will be used to expand the and deepen its enterprise customer base.

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The Bath-based company will use the funding to support its first production plant in southern Italy, which is currently undergoing stress testing ahead of commercial production expected to begin in June. The facility marks a major step toward scaling a technology that’s designed to replace plastic microparticles in everyday products.

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Tackling Microplastics At the Source

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Naturbeads, a spin-out from the University of Bath, has developed a patented process that transforms cellulose – the natural building block of plants – into perfectly round microspheres. These can be used as a direct replacement for plastic microbeads commonly found in cosmetics, detergents, paints and coatings.

Microplastics have become a growing environmental concern, particularly in products that are designed to be washed off, like body scrubs and shampoos. Once rinsed away, the particles enter waterways and can persist in ecosystems for not only years but decades on end. Naturbeads’ plant-based alternative is fully biodegradable while maintaining similar performance characteristics to traditional plastic particles.

CEO Giovanna Laudisio said the company is focused on eliminating microplastic pollution at the source while delivering a scalable solution that industries can adopt without compromising on cost or functionality.

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Scaling Production in Italy

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The €4.1 million grant will partially reimburse the construction of Naturbeads’ new production facility in Puglia, Italy, while also supporting research and development as the company moves toward full commercialisation over the next two years.

The funding comes through the European Structural Fund, which supports economic development and innovation projects across selected regions. Puglia has increasingly positioned itself as a hub for manufacturing and innovation, with access to a skilled workforce and a growing focus on industrial transition.

Naturbeads has already begun production at the plant, with the current phase focused on testing different sections of the facility before ramping up output. Once it’s fully operational, the company plans to begin serving customers globally, including ingredient manufacturers and cosmetics brands already working with the startup.

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Regulation Is Driving Demand

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The funding arrives at a time when regulatory changes are expected to accelerate demand for alternatives to microplastics. New EU rules restricting the use of plastic microparticles in cosmetics will begin rolling out over the next decade, starting with rinse-off products in 2027, followed by leave-on cosmetics in 2029 and makeup-related products in 2035.

These changes are pushing manufacturers to find sustainable replacements that can match the performance of plastics. Naturbeads is positioning its cellulose-based microspheres as a drop-in solution that works across multiple industries.

While cosmetics are an early focus, the company says the technology can also be applied to paints, coatings, adhesives, detergents, softeners and even biomedical devices. This broader application potential could significantly expand the addressable market as sustainability requirements tighten.

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From Research To Commercial Scale

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Naturbeads has spent years developing its manufacturing process, which enables continuous production of biodegradable microbeads at scale. The Italian facility represents the startup’s first major step into commercial manufacturing.

The company says it has already reached a key milestone by successfully starting production at the plant. The next phase involves completing system testing and increasing output ahead of full-scale operations.

With customers already waiting for supply, the funding provides critical support as Naturbeads transitions from mere R&D to commercial deployment.

As industries face increasing pressure to remove microplastics from products, startups like Naturbeads are moving into position to provide scalable alternatives. With new production capacity coming online and regulatory tailwinds building, the company is now focused on turning its plant-based microspheres into a mainstream replacement for plastic.

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The Helsinki and London-based company is licensed and regulated by the Finnish Financial Supervisory Authority and currently serves more than 15,000 SME customers across Europe. Adoption has tripled over the past 12 months, with particularly strong uptake in Southern Europe and the Nordics. Italy has emerged as a key growth market, and continues to be a core base.

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More Than A Business Account

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Wamo’s platform combines multi-currency business accounts, cards, invoicing and expense management in a unified interface designed for small businesses. The company is also integrating embedded lending into its platform, using real-time banking, payments and operational data to enable faster, data-driven underwriting. After launching its business loan service in Finland, Wamo plans to expand lending across Europe in Q2 2026 through strategic partnerships, targeting €100 million in lending volume over the next 12 months.

Founder Yanki Onen said the company’s ambition goes beyond digital banking: “We are integrating AI and automation across our platform to reduce friction, unlock better insights and give businesses clearer control over their finances. More than 15,000 European SMEs already bank on Wamo, and we are now on a fast track to deliver a hyper-personalised experience to many more. We want to reach 100,000 customers.”

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Why Investors Are Backing It

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Pekka Maki, Managing Partner at 3TS Capital Partners, framed the opportunity as a structural one: “SME banking in Europe is still largely broken and the opportunity for a truly is enormous. Wamo is one of the most focused teams we’ve seen tackling this problem, and their early traction in Italy and Finland validates the model.”

Ilker Sozdinler, General Partner at Oleka Capital, added: “SME banking in Europe remains underserved and fragmented. Wamo’s approach, combining intelligent automation with a focus on customer experience, positions them to capture significant market share.”

The post Wamo Raises €10m Series A To Build Europe’s SME Financial Stack appeared first on 91̽��.

The company has raised $5 million in seed funding, led by climate-focused VoLo Earth Ventures, to scale its nature-inspired algorithms, which compress massive AI models without significant loss in performance. In recent tests, Refiant compressed a 120-billion-parameter model to run on a standard MacBook Pro with 12GB of RAM, slashing energy use by over 80% compared to conventional data centre setups.

“Most solutions today focus on building bigger data centres,” says Sid Gutta, Co-Founder. “We’re taking the opposite approach: make AI smarter, smaller, and greener.”

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Efficiency Meets Impact

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Refiant’s method isn’t just a technical feat. It could transform the economics and environmental footprint of AI. The startup’s compressed models retain 95-99% of original accuracy, allowing multiple models to run on a single machine, drastically reducing electricity consumption. The implications extend beyond cost savings: organisations in regions without large data centres could run powerful AI locally, improving both energy efficiency and data sovereignty.

Google’s recent TurboQuant algorithm highlights the same trend, but Refiant achieves comparable results independently, using nature-inspired optimisation rather than brute-force scaling, according to Dr Viroshan Naicker, Co-Founder.

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Here’s Why Investors Are Excited

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For VoLo Earth Ventures, the appeal was clear: “AI’s biggest limit isn’t demand, it’s energy,” says Joseph Goodman, Managing Partner. “Refiant has found a fundamentally more efficient way to compute��– one that could make AI sustainable at scale.”

The funding will expand Refiant’s team, including engineers from Google Cloud, NASA and Cambridge, and accelerate enterprise partnerships to integrate its energy-saving AI across industries. With efficiency, sustainability and performance all in one package, Refiant is showing that green AI isn’t just possible. Now, it’s commercially viable.

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Lucida’s AI system, already deployed in the NHS, analyses MRI scans to deliver risk scores in minutes, aiming to reduce delays, unnecessary biopsies and treatment backlogs.

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Tackling a Critical Bottleneck in Cancer Care

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Prostate cancer is one of the most common cancers among men in the UK, with around 610,000 men living with the disease and only 55% diagnosed before the cancer spreads. Radiology shortages are compounding the problem, with a projected 40% shortfall in UK radiologists by 2028.

Lucida’s AI addresses this bottleneck by rapidly analysing scans and flagging high-risk cases for priority review by clinicians. The goal is faster, more confident decision-making and ultimately earlier treatment for patients.

Dr. Antony Rix, Co-founder and CEO of Lucida Medical, says: “Cancer imaging volumes are rising rapidly but reporting capacity is not keeping pace. Our goal is to give clinicians faster, more confident decisions while reducing unnecessary interventions for patients.”

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AI Is Driving Diagnoses That Are Faster and More Accurate��

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Lucida’s first AI product but the company plans to expand across other cancer types. Its platform, Pi (Prostate Intelligence), has been trained and validated on thousands of patient scans and is CE-certified for use in the UK and EU.

Already, the technology is deployed in 15 NHS hospitals, with Somerset NHS Foundation Trust reporting improved triage and reduced waiting times. If the AI flags a scan as high-risk, it triggers urgent review and rapid biopsy scheduling, potentially shaving weeks off traditional diagnostic pathways.

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This Funding Fuels Growth and Expansion

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The £8.7 million investment will support Lucida’s continued growth, including pursuit of US FDA approval and the expansion of its AI diagnostics platform beyond prostate cancer.

David Fisher, Senior Investment Director at IW Capital, highlights the opportunity: “Lucida Medical is addressing a critical bottleneck in modern healthcare. The company combines deep clinical expertise, strong NHS validation, and a scalable technology platform, and we are pleased to support its next phase of growth.”

For fintech-style investors and healthtech watchers, Lucida represents a case study in AI solving real-world operational challenges in high-stakes industries, where efficiency and accuracy are non-negotiable.

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Partnerships and Impact

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Macmillan Cancer Support, which also participated in the round, emphasises the human impact: “We need faster diagnosis alongside better awareness so men seek help earlier. Lucida Medical’s AI platform has the potential to make a very real and immediate improvement for people living with cancer,” says Anthony Cunliffe, Lead Medical Advisor.

XTX Ventures brings expertise in machine learning and operational support, helping Lucida scale effectively while maintaining clinical accuracy.

As , Lucida Medical’s approach illustrates the intersection of deep learning and clinical practice. The startup is part of a broader trend where AI is no longer experimental but operational, supporting hospitals, doctors and patients in real time.

With rising cancer rates, radiologist shortages and increasing pressure on health systems, this funding could mark a turning point. That is, transforming not just prostate cancer diagnosis but potentially the wider landscape of oncology diagnostics in the UK and beyond.

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The round also saw participation from well-known creators including Rob Landes, Charles Berthoud, Rob Van Impe and Mario Joos, the strategist behind many of MrBeast’s viral videos.

Founded by childhood friends Oscar Ferguson and Harrison Chapman, Deaku is aiming to tackle what it describes as the “missing infrastructure layer” in a Creator Economy now valued at $250 billion globally.

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Solving a Fragmented Creator Tech Stack

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Despite its rapid growth, the Creator Economy still relies heavily on disconnected tools for strategy, analytics, communication and content production.

Deaku is looking to change that by building a single, connected workspace that brings all of these elements together. The platform integrates strategy, analytics, collaboration and AI into one system, helping creators and marketing teams streamline workflows and scale output more effectively.

At the core of the platform is its context-aware infrastructure, which allows AI to understand , data and workflow. By housing everything in one environment, Deaku aims to remove guesswork and enable faster, more strategic decision-making.

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Built by Creators, for Creators

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The idea for Deaku came from the founders’ own experience working within the Creator Economy.

Ferguson, , initially entered the space to combat the spread of medical misinformation online. He partnered with Chapman, who had built a video production business working with some of the world’s largest YouTubers.

As they scaled their own operations, they encountered a common problem: a fragmented and costly stack of tools that didn’t integrate. Deaku was created as a direct response – a platform designed to replace disconnected systems with one purpose-built solution.

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Funding to Accelerate Growth

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The £480K raise will be used to accelerate product development, expand Deaku’s engineering team and strengthen support capabilities.

The company also plans to invest in go-to-market initiatives, including partnerships with leading voices in the Creator Economy.

Speaking about the raise, Co-founder Oscar Ferguson said,��“The Creator Economy has grown at extraordinary speed, but the infrastructure hasn’t kept up. Creators are forced to patch together multiple tools that don’t speak to each other. Deaku changes that. We’re building the connected workspace that creators and teams actually need – one system that understands their strategy, their data and their workflow.”

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Backed by Fuel Ventures

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Investor Mark Pearson, Founder of Fuel Ventures, highlighted the team’s industry insight as a key reason for backing the company.

“What stood out to us was Oscar and Harrison’s combination of first-hand insight into the challenges the industry is facing and product vision. They’re not just building another creator tool – they’re laying the operational foundations for how modern creator-led businesses run. Deaku is positioned to become a foundational platform in this rapidly growing sector, and we’re excited to support its growth.”

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Building the Backbone of the Creator Economy

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As the continues to expand, the need for integrated infrastructure is becoming more apparent.

While traditional media industries have spent decades developing systems and workflows, creator-led businesses are still navigating a fragmented landscape. Deaku’s approach – that is, combining AI, analytics and collaboration into one unified platform – reflects a broader shift towards platform consolidation and intelligent workflows.

If successful, Deaku could position itself as a foundational layer in the Creator Economy, helping creators and teams operate more efficiently and scale their businesses in an increasingly competitive space.

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The round was led by Picus Capital, with participation from Rabo Investments – Corporate Venturing and existing investors Inkef, GPT, Crane Venture Partners and Coatue.

The company says the fresh funding will help accelerate global expansion, product development and hiring, as it moves closer to processing one billion transactions per year and aims to handle $100 billion in annual payment volume.

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Modernising Payment Processing

Fintech Silverflow has raised $40 million in Series B funding to expand its cloud-native payments infrastructure globally as it approaches one billion transactions processed annually.

Founded in the Amsterdam , Silverflow is positioning itself as a modern alternative to legacy payment processors. Its platform offers a cloud-native, single-API infrastructure designed to simplify payment processing for banks, payment providers and commerce platforms.

According to CEO and co-founder Anne Willem De Vries, the investment reflects growing demand for payment systems built for today’s digital economy.

“This investment is a clear validation that the market is ready to move past the ‘legacy drag’ of outdated systems,” he said. “We’re the only cloud-native company targeting this specific area, and this capital will help cement our position as the new standard in payment processing globally.”

The platform is designed to help businesses simplify complex payment infrastructure, launch services faster and scale globally.

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Rapid Growth In Transaction Volumes

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Silverflow’s growth over the past two and a half years has been significant. The company has scaled from around 180 transactions per day to nearly 1.75 million daily transactions, highlighting the speed at which its platform has been adopted.

Its customer base includes major financial institutions and such as Deutsche Bank, Bolt, Payabl and Buckaroo.

These clients span acquiring banks, payment companies and fast-growing commerce platforms across Europe, North America and the Asia-Pacific region.

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Expansion Plans And Hiring

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With the new funding secured, Silverflow plans to increase its global workforce by more than 50%, expanding from 85 employees to around 120. Much of this hiring will focus on software engineering and product development roles.

Geographically, the company is looking to strengthen its presence in North America, particularly its office in New York City, while also expanding operations in Southeast Asia.

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Investor Confidence In Next-Generation Payments

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For investors, Silverflow’s approach reflects a broader shift in the payments sector toward modern, flexible infrastructure.

Florian Reichert, Partner at Picus Capital, said legacy payment processors often struggle to support innovation due to outdated architecture.

“The payments infrastructure market is defined by monolithic, slow systems that stifle innovation,” he said. “Silverflow has proven that a cloud-native, single-API approach is not just an alternative, but the inevitable evolution.”

He added that the company’s growth and customer traction demonstrate the demand for a more modern payments stack.

Floris Onvlee, Director of Corporate Venturing at Rabo Investments, also highlighted the importance of supporting with global ambitions.

“As an EU-based investor, we’re proud to support Silverflow as a European champion as it continues its global expansion,” he said.

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Expanding Payment Network Support

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On the product side, Silverflow plans to expand support for additional global card networks, including China UnionPay and JCB.

These will complement its existing integrations with major payment networks such as Visa, Mastercard, American Express, Diners Club International and Discover.

The company also plans to invest in new front-end tools and user interfaces to make its API-driven platform easier for customers to use, while expanding capabilities to better support in-store payments alongside online transactions.

As global commerce continues to digitise, Silverflow is betting that modern infrastructure will become essential for payment providers and banks looking to scale internationally.

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The round was backed by Altair, DVC, Yellow Rocks, Finom co-founder Kos Stiskin, ManyChat co-founder Mike Yan and a group of and angel investors. According to the company, the fresh capital will be used to accelerate the rollout of �ʱ��ܰ�����’s AI agent, which it describes as acting across channels as a full performance marketer.

The funding comes at a time when advertising and marketing software markets are continuing to expand. Global ad spend is forecast to rise 5.1% in 2026 to surpass $1.04 trillion, while the performance marketing software market is projected to grow from $15.2 billion in 2023 to $30.9 billion by 2032, driven in part by AI-led automation and optimisation.

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From Dashboards To Decisions

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Plurio is positioning itself around a familiar frustration for marketing teams: fragmented tools and delayed feedback loops.

For consumer software and service brands, performance decisions often hinge on metrics that only become clear days or even weeks after campaigns are launched. Trial activations, qualified leads, subscription starts and revenue figures typically lag behind ad spend. In that environment, teams can find themselves waiting for confirmation before acting, even though small timing differences can materially affect customer acquisition costs.

�ʱ��ܰ�����’s is designed to intervene earlier in that process. The system analyses early signals such as creative performance shifts, audience quality changes and channel behaviour to infer likely downstream outcomes before final conversion data arrives. It aims to identify when a creative is beginning to fatigue, when a new trend is emerging or when a budget shift could improve performance.

In early pilot programmes with global EdTech and FinTech brands, the company says the platform processed $20 million in ad spend over four months, delivering 2x sales growth and more than 20% lower customer acquisition costs. Those results prompted the team to double down on developing the agent further.

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An evolution from Elly Analytics

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Before rebranding, the company operated as Elly Analytics, a marketing data platform that managed over $100 million in annual ad spend. That infrastructure now sits within the broader Plurio ecosystem.

The platform integrates advertising, CRM and revenue data into a single system, either plugging into a brand’s existing analytics stack or using its own built-in marketing data platform with attribution capabilities. Teams interact with the agent through natural language prompts, asking scenario-based questions such as how revenue might shift if budget is reallocated between channels, or instructing it to pause campaigns below a certain return on ad spend.

Behind the scenes, the system evaluates factors including seasonality, audience quality, funnel efficiency and revenue trends. It can recommend changes, forecast potential outcomes and execute approved adjustments. The company describes this as a closed-loop optimisation process, where the model learns from each cycle and refines future predictions.

CEO and co-founder Seva Ustinov says the idea emerged from years of watching marketing teams spend most of their time consolidating data rather than shaping strategy. Co-founder and Chief Growth Officer Kirill Kasimskiy adds that the goal was to bridge the gap between insight and action, rather than introduce another standalone dashboard.

With and a growing market for AI-driven marketing tools, Plurio is now focused on scaling its agent and expanding its footprint among performance-led consumer brands.

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