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Trent AI raises $13M to bring agentic AI security to enterprise workflows

The rapid adoption of autonomous AI agents across enterprise environments has created a significant and largely unaddressed cybersecurity gap. According to Deloitte’s 2026 State of AI report, nearly three in four companies plan to deploy agentic AI within two years, yet only one in five has a mature governance model for autonomous agents. London-based Trent AI has emerged from stealth with a $13 million seed round to tackle this structural vulnerability head-on, offering what it describes as the first multi-agent security solution purpose-built for the agentic era.

The seed round was co-led by LocalGlobe and Cambridge Innovation Capital, with participation from senior figures at OpenAI, Spotify, Databricks, AWS, and Stripe. The capital will be deployed to expand the engineering team, accelerate product development, and grow Trent AI’s early customer base across Europe and the United States.

LocalGlobe and Cambridge Innovation Capital back agentic AI security play

The calibre of Trent AI’s investor roster reflects the seriousness with which the industry views the agentic security challenge. LocalGlobe, one of Europe’s most prominent early-stage venture firms, co-led the round alongside Cambridge Innovation Capital, the University of Cambridge’s venture arm. The angel investor list reads as a who’s who of senior AI leadership: Joaquin Quiñonero Candela, a member of technical staff at OpenAI; Tony Jebara, former Vice President of Engineering and Head of AI/ML at Spotify; Ippokratis Pandis, a Distinguished Engineer at Databricks; and Avinash Bhat, a Director at AWS.

The founding team brings deep technical credibility to the challenge. CEO Eno Thereska previously served as Distinguished Engineer at Alcion, AWS, and Confluent. Chief Scientist Neil Lawrence holds the DeepMind Professorship of Machine Learning at the University of Cambridge and previously served as Director of Machine Learning at Amazon. CTO Zhenwen Dai brings experience as a machine learning scientist at AWS and Senior Research Manager at Spotify.

A platform built to secure autonomous AI agents

Unlike conventional cybersecurity tools retrofitted for AI environments, Trent AI’s platform deploys specialised AI security agents that continuously scan customer environments, assess risk, mitigate vulnerabilities, and evaluate overall security posture. The system operates through four distinct agent groups handling vulnerability detection, severity ranking, remediation recommendations, and security trend analysis.

The platform’s proprietary judgement layer and reinforcement learning technology orchestrate these security agents across customer workflows, transforming agentic AI security from a manual audit exercise into a continuous, automated process. Trent AI’s agents can simulate complex attack chains, detect overly broad access permissions, and generate actionable code improvement suggestions — capabilities that static rule-based security tools fundamentally lack.

The platform already integrates with popular AI development tools including Claude Code and Lovable, and supports CI/CD pipeline integration for continuous security monitoring. Trent AI has been adopted by several technology firms during its stealth period, with early design partners including Canopy and Weblogic.

European agentic AI security market gains momentum

Trent AI’s emergence comes at a time when the European cybersecurity market is experiencing substantial investment momentum, driven in part by regulatory frameworks such as the EU AI Act that place increasing obligations on organisations deploying autonomous AI systems. The gap between agentic AI adoption and adequate security infrastructure represents a significant market opportunity, particularly as enterprises move beyond experimental deployments toward production-grade autonomous workflows.

The $13 million seed round positions Trent AI among the better-capitalised European cybersecurity startups at the pre-Series A stage. With AI agent deployment accelerating across sectors from financial services to healthcare, the demand for purpose-built agentic security solutions is expected to grow substantially in the coming years.

For more on European startup fundraising, visit our fundraising coverage.

Summary

Company Trent AI
Headquarters London, United Kingdom
Founded 2025
Round Seed
Amount $13 million
Lead Investors LocalGlobe, Cambridge Innovation Capital
Notable Angels Leaders from OpenAI, Spotify, Databricks, AWS, Stripe
Use of Funds Engineering expansion, product development, customer growth

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London-based AI laboratory Ineffable Intelligence has emerged from stealth with a $1.1 billion seed round at a $5.1 billion post-money valuation, the company confirmed on 27 April 2026. The financing is the largest seed round ever raised by a European company and one of the largest first-money-in rounds in the global history of artificial intelligence. The round was co-led by Sequoia Capital and Lightspeed Venture Partners. Participating investors included Nvidia, DST Global, Index Ventures, Google, and the UK Sovereign AI Fund, the British government’s recently established vehicle for backing strategic AI capacity on home soil. A bet on a different path to general intelligence Ineffable Intelligence was founded in 2025 by David Silver, the former Vice President of Reinforcement Learning at Google DeepMind and the principal architect of AlphaGo, AlphaZero and AlphaStar. He is joined by three further DeepMind alumni: Wojciech Czarnecki, Lasse Espeholt and Junhyuk Oh. All four have spent the past decade at the frontier of reinforcement learning research, the discipline behind some of the most consequential demonstrations of machine learning over the past ten years. The company describes its objective as building a “superlearner” — an AI system capable of acquiring knowledge directly from its own experience rather than from human-generated text or imagery. “Our mission is to make first contact with superintelligence,” Silver said in a statement accompanying the launch. “We are creating a superlearner that discovers all knowledge from its own experience, from elementary motor skills through to profound intellectual breakthroughs.” The framing is a deliberate departure from the dominant industry trajectory. Most leading AI laboratories, including OpenAI, Anthropic and Google DeepMind itself, have built large language models trained primarily on the corpus of the internet, then refined that training with human feedback. Ineffable’s wager is that the marginal returns on scaling text-based pretraining are diminishing and that the next leap in capability will come from agents that learn endlessly from the consequences of their own actions, in much the same way AlphaZero learnt the game of Go without studying any human matches. Why $1.1 billion at seed The size of the round is unusual even by the inflated standards of the 2026 AI capital cycle. Two factors appear to explain it. First, frontier reinforcement learning at the scale Ineffable describes is computationally extraordinarily expensive: the company will need to operate vast simulation environments and train very large models against them, an undertaking that consumes capital at a rate closer to physical R&D than to traditional software. Second, the round signals a strategic move by Europe’s investor and policy ecosystems to retain the most ambitious AI researchers on the continent. The presence of the UK Sovereign AI Fund alongside Sequoia, Lightspeed and Nvidia is the clearest expression of that intent. The British government has publicly framed the investment as a bet on breakthrough AI that “can discover new knowledge”, positioning the country as a willing co-investor in domestic frontier laboratories. For Ineffable, the implication is access not only to capital but to compute, regulatory engagement and the still-resilient academic talent base around UCL, Oxford, Cambridge and Imperial. Founder pledge of historic scale Alongside the funding announcement, Silver disclosed that he is committing 100 per cent of any personal proceeds from his Ineffable equity to charity via the Founders Pledge network — described by the organisation as the largest pledge in its history. At the round’s $5.1 billion valuation, that commitment could ultimately exceed several billion dollars if the company succeeds. It is a meaningful gesture in a sector where the reputational stakes around concentrated AI wealth are escalating, and one likely to be referenced in subsequent founder-led commitments. Implications for the European AI landscape Ineffable’s emergence reshapes the European AI map in three concrete ways. It establishes London as the home of the continent’s largest-ever seed-stage company, complicating Paris’s recent narrative of frontier-AI primacy after Mistral’s earlier rounds. It validates a thesis — that reinforcement learning, not transformer scaling, is the next frontier — that has lately been losing capital share to language-model incumbents. And it confirms that the UK government is now willing to act as a balance-sheet co-investor in domestic AI laboratories, a posture much closer to the French model than to the predominantly grant-based regimes elsewhere in Europe. The execution risk is non-trivial. 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