Memory that earns its shelf space
Episodic recall, consolidation, associative memory, user context, and world models—so agents can carry useful experience forward without turning every past detail into permanent truth.
↗XAGI Labs builds advanced intelligence—and secures the future it creates. We develop the memory, perception, execution, and evaluation systems that move agents toward AGI, alongside the adversarial testing and evidence infrastructure required to keep increasingly capable AI accountable.
ATLAS OS and TRUSCOR are separate products informed by this research. Neither sits above the other.
We advance the systems that make agents more capable and the evidence infrastructure that makes their power understandable, testable, and accountable.
Episodic recall, consolidation, associative memory, user context, and world models—so agents can carry useful experience forward without turning every past detail into permanent truth.
↗Accessibility trees when structure is available; OCR and visual grounding when it is not. Then outcome checks to see whether the click actually worked.
↗Playwright and a real-Chrome bridge, accessibility scanning, cached action paths, and recovery when pages drift.
↗Evaluate memory, routing, task completion, and token efficiency. Explore candidates. Reject unsafe patches. Roll back when improvement is only impressive on paper.
↗We research product-specific foundation models, learned multi-model orchestration, and general-purpose intelligence designed to expand what capable agents can understand and accomplish.
↗Capability without human authority is just a faster way to be wrong. We design for scope, restraint, inspection, reversibility, and honest limits.
Identity, tenancy, permissions, and context should come from trusted boundaries.
People should be able to inspect, approve, deny, mute, disarm, and reverse.
An action is not complete because an API returned 200. The real state has to change as intended.
Research is not a product promise. A roadmap is not a benchmark. Limitations belong above the fold.
We do not believe AGI becomes useful by becoming mysterious. It becomes useful when it can understand context, act carefully, learn without quietly rewriting the rules, and stay accountable to the people living with it.
Ambition gets the big whiteboard. Safety gets the permanent marker.
— XAGI Labs
Read the full manifesto →ATLAS OS and TRUSCOR address different needs in the agentic era. Each has its own mission, product page, website, and operating boundaries.
The AI operating system for companies—shared context, specialist agents, and governed work that moves toward outcomes.
The neutral evidence layer for AI systems—live adversarial testing and reproducible evidence for third parties.
Research collaboration, safety work, product questions, press, or a thoughtful hello—we read the messages ourselves.
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