Unicity Labs raises €2.5 million for secure AI agent networks
Swiss startup Unicity Labs has secured €2.5 million in fresh funding to develop a new peer‑to‑peer cryptographic architecture designed specifically for autonomous AI agents. The investment will support the company’s mission to enable machines to communicate, negotiate and transact directly with one another in a secure, verifiable, and privacy‑preserving way.
Building a trust layer for autonomous AI
As large language models and autonomous AI systems move from experimentation into production, enterprises are grappling with how to control, audit and secure the growing number of machine‑to‑machine interactions. Unicity Labs is positioning its technology as a foundational “trust layer” for this emerging machine economy.
The startup’s architecture uses distributed public‑key cryptography, zero‑knowledge proofs and peer‑to‑peer networking so that AI agents can authenticate each other, sign and verify actions, and share data without relying on a single central authority. This approach aims to reduce systemic risk, limit single points of failure, and give organizations stronger guarantees over who did what, when, and under which policy constraints.
Why peer‑to‑peer cryptography matters for AI
Today, most deployed AI services are routed through centralized platforms, which raises concerns around data privacy, security, and vendor lock‑in. By contrast, a peer‑to‑peer model allows AI agents to operate closer to where data is generated — in industrial systems, financial infrastructure, or consumer devices — while still enforcing strong identity and access control guarantees.
For sectors such as finance, healthcare, and critical infrastructure, this kind of verifiable autonomy could be crucial. Organizations need AI that can act on their behalf, yet remain fully auditable for regulators, partners, and customers.
Positioning within Europe’s AI and cryptography landscape
With this €2.5 million round, Unicity Labs joins a growing cohort of European startups working at the intersection of AI safety, distributed systems and advanced cryptography. The company plans to use the capital to expand its engineering team, harden its protocol, and launch pilot projects with early enterprise adopters who are exploring agent‑based automation.
As policymakers in Europe push for stricter rules around AI governance and data protection, demand is rising for infrastructure that embeds compliance and security at the protocol level. Unicity Labs is betting that the future of AI will depend not only on smarter models, but on the cryptographic rails that allow those models to operate safely at scale.