UniMem.

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The memory loop · remember, measure, governHow UniMem connects persistent agent memory to randomized outcome measurement, review, withdrawal, promotion, and rollback.Developers · quickstart & integrationsInstall locally. Connect Codex, Claude Code, Cursor, Windsurf, Python, or HTTP.Enterprise · deployment & governanceExplore UniMem local and self-hosted deployment, scoped memory, configurable review, and a focused enterprise pilot.The next session should inherit the lesson.Use UniMem for persistent coding-agent context, reviewed project lessons, and outcome measurement across repeated engineering tasks.Shared memory needs shared boundaries.Scope shared agent memory, review conflicting changes, and use opt-in stale-generation checks in UniMem multi-agent workflows.Persistent context. Accountable change.Plan a bounded UniMem pilot for enterprise agents with local deployment, reviewed memory, access boundaries, and verified outcomes.Documentation · setup, interfaces & guaranteesA curated UniMem documentation index for local setup, measurement, promotion, team isolation, safety, and deployment guarantees.The agent memory problem.Why persistence and retrieval are only part of agent memory, and why long-lived agents need a feedback loop for remembered experience.Memory and context do different jobs.Understand context windows, persistent agent memory, retrieval, and the lifecycle controls needed between storage and agent behavior.Evaluate what memory changes.A practical guide to evaluating agent memory with stable task IDs, eligible-memory holdouts, complete outcomes, and integrity checks.Platform · one governed memory systemThe UniMem platform: lessons, bitemporal facts, knowledge graph, conversations, memory blocks and procedures; hybrid multi-hop retrieval; randomized evidence; governance; MCP, HTTP, Python and ROS 2 interfaces.Physical AI · robots & fleetsUniMem for physical AI: planner context and durable outcomes for robots, in-loop working memory, a bounded STL shield on memory-derived actions, collective site memory and living safety cases.Vision · memory for intelligent machinesWhy every agent and robot will need a governed memory, why that memory must prove it helps, and what UniMem is building toward.Benchmarks · evidence & methodologyUniMem conversation memory measured end to end on LoCoMo, LongMemEval and BEAM: retrieval, answer accuracy, serving latency, reproduction commands and honest caveats.Investor overviewUniMem is raising to build memory infrastructure for AI agents and robots. Explore the product, published benchmarks, commercial strategy, and next milestones.About UniMemUniMem’s mission: give long-lived AI agents persistent, reviewable memory connected to evidence from future work.Learn · field notesGuides to agent memory, context, and evidence.Contact · explore a pilotBring one workflow and one real memory problem.
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Last updated: October 31, 2026.

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Interactive demonstrations explain product behavior using included example records and simulated outcomes. Published benchmarks have the scope and limitations stated alongside them. Neither demonstrations nor benchmark results promise outcomes for your deployment.

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