An unbroken memory for AI-native engineering.
Agents need what teammates need: shared, persistent, trustworthy context. Continuum provides it as infrastructure — a semantic memory your repos flow into and your agents draw from, with a workflow that keeps it current and a contract that keeps it honest.
Everything your work produces, in one store.
Continuum is built on Engram, our proprietary MCP server and ingest toolchain. Repositories are ingested — source, documentation, session notes, git commit history — chunked, embedded, and stored in a database that belongs to you alone. The memory is searchable two ways: semantically, when you know what you mean but not where it lives, and by exact text, when you know precisely the identifier or error string you're hunting. Multi-repo by design: one memory spans every repository you give it, so "how did we deploy this last time" is answerable from anywhere.
MCP server for codebase context.
The memory speaks Model Context Protocol. Any MCP-compatible coding agent authenticates over OAuth 2.1 and receives the same tools: semantic search, exact-text grep, file summaries, repository and file listings, and the activity log of past sessions. Because the contract is the protocol, there is no agent lock-in — your context outlives any individual tool, model, or vendor decision.
The workflow that writes memory.
A Continuum session opens by reading: the agent queries memory for the decisions, conventions, and history that govern the work. It closes with a ritual: a session note recording what happened and why, a commit that references it, an ingest that writes both into memory, a push. The close writes what the next open reads — any agent, any week, picking up the thread exactly where it was set down.
The loop is the moment of memory: the line doubles back on itself without breaking.
Wrong answers fail loudly.
A memory system has exactly one fatal failure mode: the silent wrong answer — the confident "no results" that should have been a result. Continuum is engineered against that class specifically. Unknown scopes are errors, not empty lists. Limits are documented policy, not surprises. Empty means empty. The retrieval contract is adversarially smoke-tested against production, because memory you can't trust is worse than no memory at all.
// adversarial smoke run 001, finding MED-2 — production memory, verbatim
BUG — nonexistent repo yields silent empties on all four repo-scoped tools. A typo'd repo is indistinguishable from a genuine no-match — the "silent artifact" failure mode the contract warns about.
// the fix, pinned by test — exact wording asserted
Unknown repo 'X'. Use list_repos to see available repos.
// smoke run 002: unknown-repo uniformity ×5 — PASS
This finding, the fix, and the regression test all live in the same memory — the system's own bug history is queryable through the tools it describes.
Code is the first corpus.
Continuum works on code today because that's where we live — but the memory underneath is a general engine for structured knowledge. Technical publications fit it naturally — S1000D data modules and IETM packages arrive pre-chunked, versioned, and reuse-oriented: retrieval over structured content, provenance attached, reuse surfaced before duplication happens. If your organization's knowledge is structured and your tolerance for losing it is zero, the door is open. Continuum for technical publications →