Trent AI, an agentic security company, today announced its emergence from stealth with a layered security solution built for the agentic era. Following a $13M seed round led by LocalGlobe and Cambridge Innovation Capital, with participation from leaders at OpenAI, Spotify, Databricks, AWS and others, the product is the first multi-agent security solution designed to secure agents as they evolve. Led by strong conviction that security should be continuous, invisible and scalable, Trent AI’s leadership team brings deep experience from Spotify, AWS, Alcion (acquired by Veeam) and Confluent.
“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,” said Eno Thereska, Co-founder and CEO of Trent AI. “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.”
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According to Deloitte’s 2026 State of AI report, nearly 3 in 4 (74%) companies plan to deploy agentic AI within two years. Despite this, only 1 in 5 (21%) report having a mature model for governance of autonomous agents. The threat increases in complex environments with interconnected agents, with security holes risking the entire infrastructure;driving the need for a security and compliance solution that encompasses the entire agentic ecosystem.
Trent AI’s Unified Security Solution
Built for developers and security teams that want to develop and ship agents fast without compromising security, Trent AI’s layered, unified offering secures agents throughout the entire lifecycle. Every cycle makes Trent AI’s agents smarter about the systems they protect. As the feedback loop tightens, judgement improves and mitigations become more accurate, giving development and security teams a faster, more reliable path to safe deployment. Agents in the loop work to:
- Scan: These threat scanning agents continuously observe code, infrastructure, dependencies, agents and runtime behavior, learning where risk lives in your ecosystem, laying the framework for security by design.
- Judge: These analysis agents determine and classify signal vs. noise, assess business impact and prioritize based on real risk rather than static rules. This judgement becomes more predictive over time.
- Mitigate: These remediation agents patch vulnerabilities, open pull requests, adjust configurations and validate that fixes work for a healthier code base.
- Evaluate: These security posture agents track trends, quantify risk over time, benchmark against standards and identify systemic weaknesses for a compounding framework that becomes increasingly more accurate at conducting risk forecasts.
Design partners, companies with early access to the Trent AI agentic security solution, including Canopy, Commscentre, ML@Cam, Qbeast, Weblogic and others are already seeing tangible benefits to security and deployment. These partners have reported: immediate visibility into their security posture, a security audit report, fast response time identifying and presenting vulnerabilities, a clean and well laid out remediation scope and adaptive feedback.
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