Responsible AI, from research to runtime.

Praxi Labs is an independent AI research lab building the tools, systems, and infrastructure that make modern AI safe, accountable, and useful in practice. We work across the full AI stack, from foundational research on alignment and evaluation to the runtime systems that govern how AI is deployed in the real world.

Responsible AI Frameworks, benchmarks, and tooling for evaluating AI systems against the qualities that matter most: safety, fairness, transparency, robustness, and accountability.

AI Agents and Autonomy Infrastructure for the next generation of agentic software including composition, sandboxing, verification, and policy enforcement for systems that act on behalf of users.

Alignment and Evaluation Empirical research into how AI models behave under adversarial pressure, distribution shift, and real-world deployment conditions, and how to measure when they fail.

Applied AI Systems Usable products and developer-facing tools that put responsible AI research into the hands of practitioners, not just papers.

Decentralized Trust Layer for AI Agent Skills. A Bittensor subnet that turns untrusted AI agent skill bundles into Signed Skill Safety Attestations — portable, cryptographically signed artifacts with enforceable execution policies. Real sandbox detonation. Evidence-gated scoring.

Phylax (φύλαξ): Ancient Greek for guardian, sentinel, watchman.

More projects coming soon across alignment, evaluation, and applied AI.

Evidence over assertion. Claims about AI safety should be backed by verifiable traces, not vibes.

Open by default. Research that shapes how AI is deployed should be inspectable by the people it affects.

Adversarial mindset. Systems that don't survive adversarial pressure aren't safe, they're untested.

Useful, not ornamental. Responsible AI is a property of shipped systems, not a marketing checkbox.

Browse our repositories, open an issue or discussion on any active repo, or reach out directly. Contact details coming soon.

_{Praxi Labs · Responsible AI · Agents · Alignment · Evaluation}