V0.1.0 · HELSINKI RELEASE

The self‑governing memory layer for agents

One MCP server connection.
Engrammic remembers, recalls, traces, and synthesizes relevant context for your agents while you prompt.

memory is flat. meaning is engrammic.

THE PROBLEM

Big context windows, RAG, and LLM Wiki all hit the same wall.

01

Context window

Context gets compressed and loses nuance after context window filled.

02

RAG / GraphRAG

Retrieval doesn't solve provenance, fails in real decision making.

03

LLM Wiki

Md files grow fast. Breaks down quickly with bigger workflows.

04

Vector memory

Conflicting entries unresolved, irrelevant data stays, creating noise.

None of them track what was concluded, from what evidence, and whether it still holds.

the wager

Context rot is what kills agents. Self-governing memory let agents scale.

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memory that compounds, with receipts.

01 / 03

automatic remember & recall.

Stop re-pasting context. Your agent pulls what it already knows about this topic, adds today's conclusion, and moves on.

fewer tokens · same answer

Cursor — Agent · Composer
02 / 03

answers with cited sources.

Every claim links back to the observations that support it. Ask "why?" and the agent walks you down the chain.

reliable answers with provenance

Cursor — Agent · Composer
03 / 03

supersede & synthesize.

Contradictions don't pile up. Engrammic merges conflicting positions by source quality, retires the losers, and keeps one canonical answer.

one source of truth · not three

Cursor — Agent · Composer
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how to use

one MCP server. every agent.

Install once. Your agents share memory across sessions, projects, and tools. That's the whole setup.

installcurl
curl -fsSL https://get.engrammic.ai | sh
or add manually
terminal
claude mcp add engrammic --transport http https://beta.engrammic.ai/mcp/
read the docs ↗works with claude · cursor · windsurf · cline · gemini
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benchmarks

we measure what actually compounds.

soon
results pending
financial QA

Making LLMs understand financial documents better

Benchmark in progress. We're running Engrammic against SEC filing QA on our internal harness. Full results coming soon.

in progress

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faq

questions, answered.

Shared agent memory with evidence. Agents store observations, attach claims to sources, and recall structured knowledge across sessions and tools. One MCP server, no raw dumps.

invitation

join the waitlist.

A small, considered list. Early access for teams shipping with agents.

by joining you agree to our privacy policy.

building withAntler · Helsinki