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Asymptote Labs Raises $5.5 Million to Build Security Infrastructure for AI Agents

October 20, 2026
By
Loren Baker
Asymptote Labs Raises $5.5 Million to Build Security Infrastructure for AI Agents

Asymptote Labs, a startup developing security and monitoring technology for AI agents, has raised $5.5 million in an oversubscribed seed funding round led by Tower Research Ventures.

The round also included Lytical Ventures, 1984 Ventures, and South Park Commons. The company will use the funding to expand its engineering team, develop its products, hire new employees, and grow its market presence.

Founded by Justin D’Souza and Shukan Shah, Asymptote Labs is building technology that helps businesses monitor and control AI agents. These agents can perform tasks such as writing code, accessing company data, and working across business systems. However, their growing use creates security risks when companies cannot easily track their actions.

To address this challenge, Asymptote has developed Beacon, an open-source tool that collects and organizes activity data from AI agents. It supports tools such as Claude Code, Codex, and Cursor, along with more than 20 other AI agent systems.

Beacon gives businesses a unified view of AI agent activity while allowing them to retain control of their data. It also helps developers carry useful information and lessons from previous coding sessions into future work.

The company is building its enterprise security platform on top of Beacon. The platform monitors AI agents in real time, detects potentially risky actions, and applies security rules to help prevent data leaks, insider threats, and other problems.

“AI agents are becoming a new operating layer inside every company, but the infrastructure to understand and control them hasn’t caught up,” said Justin D’Souza, co-founder and CEO of Asymptote Labs. “We saw this problem firsthand when building agents at Doppel. As companies deploy thousands of agents across their infrastructure, their runtime data will become one of the most valuable assets they own. We built Beacon as open source because we believe every organization should own that data, and Asymptote enables them to act on it.”

Asymptote reported strong developer interest in Beacon, with GitHub stars growing by more than 460% in September 2026. The project also reached No. 3 on GitHub’s global trending repositories list.

The founders previously worked at Doppel, a company focused on social engineering defence. Their experience in cybersecurity and automation helped shape Asymptote’s focus on protecting businesses as they adopt AI agents.

“What gave us confidence in Justin and Shukan was how clearly they saw the infrastructure gap emerging around enterprise AI agents,” said Lucas Nelson, Managing Partner at Lytical Ventures. “Every company will run multiple agent harnesses across teams and environments, yet there is still no shared telemetry layer that gives organizations a complete view of that activity. Asymptote is building that system of record.”

“We found the Asymptote team through Beacon, and it was immediately clear they understood the security risks of AI agents better than anyone we’d seen,” said Jared Young, Director of Venture Capital at Tower Research Ventures. “Now our security team is putting Beacon through its paces on our own endpoints, because as agents take on real work, visibility and control over what they do can’t be an afterthought.”

“As early investors in Cline, we’ve seen this kind of developer pull before,” said Ramy Adeeb, Founder at 1984 Ventures. “Agent activity is exploding across harnesses, while the context and learnings from those sessions stay fragmented. Beacon’s recent inflection reinforced our belief that Asymptote can become foundational infrastructure for teams building self-improving agent workflows.”

Although security is its initial focus, the startup sees opportunities to help engineering teams improve reliability, manage AI adoption, and control spending on AI tools.

With its latest funding, Asymptote Labs aims to expand its platform as businesses look for better ways to monitor, secure, and manage AI agents at scale.

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