Trent AI secures £9.8m to build continuous security for autonomous AI agents
This article covers Trent AI, a cybersecurity startup, raising £9.8m ($13m) in a growth funding round to build continuous security for agentic AI systems as organisations begin deploying autonomous agents at scale. The funding is intended to accelerate product development and partnerships to secure agent lifecycles across code, infrastructure and runtime behaviour, supporting enterprises adopting autonomous workflows.
Trent AI, a cybersecurity startup, has raised £9.8m ($13m) in a growth funding round to build continuous security for agentic AI systems as organisations begin deploying autonomous agents at scale. The London-based company says the funding will accelerate product development and partnerships aimed at securing agent lifecycles across code, infrastructure and runtime behaviour.
Why it matters
Adoption of agentic AI is accelerating inside enterprises, but governance and security frameworks are lagging. Deloitte’s 2026 State of AI report cited by Trent AI finds 74% of companies plan to deploy agentic AI within two years while only 21% report mature governance for autonomous agents. That gap creates an attack surface that can cascade across interconnected systems, increasing the need for tools that observe and enforce safety continuously rather than relying on periodic reviews.
The funding is notable because it brings mainstream venture capital and tech-industry operational leaders into a category that is still nascent: security for autonomous, multi-agent workflows.
Inside the product
Trent AI offers a layered, unified platform that inserts agentic security throughout the development and deployment lifecycle. The company describes four agent types that form a feedback loop:
- Scan agents continuously observe code, dependencies, infrastructure and runtime behaviour to map where risk appears.
- Judge agents analyse and prioritise findings, separating signal from noise and assessing business impact.
- Mitigate agents propose and apply remediations, from patches to configuration changes and pull requests, and then validate fixes.
- Evaluate agents track posture over time, benchmark against standards and identify systemic weaknesses to improve predictive risk assessments.
Early design partners including Canopy, Commscentre, ML@Cam, Qbeast and Weblogic report faster visibility into security posture, structured remediation scopes and quicker vulnerability identification. These partners give Trent AI live environments to refine detection, prioritisation and automated remediation workflows.
Who are the investors?
The round was led by LocalGlobe and Cambridge Innovation Capital, with participation from a roster of prominent angels and industry engineers, including Joaquin Quiñonero Candela (OpenAI), Avinash Bhat (Director at AWS), Ippokratis Pandis (Databricks), Tony Jebara (former Spotify VP Engineering and Head of AI/ML) and others from Databricks and Spotify.
In the announcement, Ian Lane, Partner at Cambridge Innovation Capital, said:
Agent adoption is outpacing enterprise security readiness. As autonomous workflows make decisions across critical systems, a new layer of infrastructure is needed to govern, observe, and enforce safe behavior. We believe Trent AI is well placed to define this category.
In the announcement, Saul Klein, Co-founder and Executive Chairman of Phoenix Court, said:
The rise of agents goes hand in hand with the rise of new security threats. Now is the right time to build the long-term foundations of security for agentic systems. Trent AI is uniquely positioned to do this, combining deep academic expertise with real-world experience building large-scale systems and working closely with design partners deploying agents today.
In the announcement, Avinash Bhat, Director at AWS, said:
Agentic systems are quickly becoming part of the software stack, but the security infrastructure around them is still early. Trent is building the foundations teams will need, to operate these systems safely at scale. I’m excited to support Eno and the team as they tackle this emerging challenge.
In the announcement, Tony Jebara, former Spotify VP Engineering and Head of AI/ML, said:
AI models have led to an exponential growth in code being generated by companies big and small. That code brings along an exponential growth in security risks, vulnerabilities and threats... and human security teams just can't keep up. We desperately need specialized AI models that can analyze this flood of code, produce security assessments and provide mitigations. Trent AI is providing just that: securing your code at all stages, all the way from the initial design stage to large code repositories.
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Founder perspective
In the announcement, Eno Thereska, Co-founder and CEO of Trent AI, said:
Organizations are deploying AI agents and autonomous workflows faster than their security can adapt, and most development teams using these agents and workflows have no security framework designed for their systems. This is not an easy problem to solve. Trent AI is tackling these difficult and important problems, while building the necessary security foundations and frameworks for agentic systems now and through the next decade.
Thereska and the leadership team draw on operational experience from Spotify, AWS, Alcion and Confluent, which they say helps when designing systems intended to operate inside complex, production-grade environments.
The bigger picture
Trent AI’s raise signals investor appetite for tooling that addresses the new class of risks introduced by autonomous agents. The round mixes traditional VCs, deep-tech investors and senior engineers from major AI platforms, reflecting both commercial and technical interest in the space.
The company is engaging with established security bodies and academic networks, including OWASP and Carnegie Mellon University’s CyLab Venture Network, and is contributing a security agent for open-source platforms such as OpenClaw. That combination of industry partnerships and ecosystem engagement is typical of UK startups aiming to bridge research-grade capabilities and enterprise readiness.
As agentic AI spreads across the UK and Europe, vendors that can demonstrate reliable observability, governance and automated remediation will be a central part of enterprise risk planning. Trent AI’s funding marks one more signal that investors are prioritising infrastructure to protect fast-evolving AI systems.
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