← Selected work

AI memory & continuity

Mnem.OS

Reviewable memory and continuity for AI workflows

Implemented internal productHyperion Industries / founder-led project
Mnem.OS — workflow architecture
Workflow architecture
THE PROBLEM

Carry useful context forward.

AI workflows repeatedly lose useful context between sessions. Simply saving every message can mix observations with trusted facts and make later decisions difficult to explain.

THE APPROACH

What I worked on.

  • Scoped memory objects and context packets with source references, confidence, exclusions and audit traces.
  • Agent lifecycle events and review-required memory proposals that remain separate from accepted durable knowledge.
  • Operator review, contradiction visibility and recovery snapshots alongside MCP and REST integration surfaces.
WHAT THE PROJECT DEMONSTRATES

The implementation includes bounded SQLite-backed search, context packing, agent continuity records, review bundles and recovery routes. Tests exercise sensitivity exclusions, scope isolation, review-required proposals and recovery behavior.

CURRENT SCOPE

Internal continuity product. Reviewable, scoped memory and local search; not an unrestricted background collector or autonomous source of truth.

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