copepodOne durable memory, assembled from conflicting context without making agents coordinate first.
Agents, people, tools, and documents all contribute partial—and sometimes contradictory—context. Copepod keeps each signal’s source, timing, and tenant context intact before asking anything to agree.
Retrieval is only useful when the underlying memory is trustworthy. Copepod keeps the write path, knowledge graph, enrichment, and governance in one coherent model.
Traverse entities, co-occurrence, and typed relationships already present in your memory graph.
Queue-Consolidate-Resolve turns simultaneous agent writes into one canonical state, with policy-driven conflict handling and provenance intact.
Move from local graph signals to LLM reasoning and web grounding only when permissions allow.
PostgreSQL RLS, envelope encryption, audit evidence, and tenant boundaries on every operation.
Define knowledge shapes, store partial objects, and let governed workers fill the gaps over time.
Expose memory operations as tools to any MCP-compatible client without another integration layer.
Agents write immediately. Copepod groups related events, detects contradictions, resolves them with policy, then commits a canonical state atomically.
Accept and tenant-scope every event.
Group writes by memory node and context.
Apply policy with provenance preserved.
Publish one explainable state to every agent.
Start with local graph signals. Add structured reasoning or web grounding only when the tenant, plan, and policy permit it.
Copepod manages reliable AI enrichment with DeepSeek V4 Flash. Each plan includes a fixed monthly allowance, with no surprise overages.
For individual builders and evaluation.
For small teams shipping their first agent workflow.
For production teams with a growing agent workload.
For high-volume, security-sensitive, or tailored deployments.
Start free, connect through MCP or the API, and let Copepod handle the hard part of shared memory.