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Memory governance for AI agents

Memory your agents can be trusted with.

Gromani is building a memory layer that sits between an agent and its memory store, designed to keep long-running work accurate as information changes. It decides what to retain, update, forget or escalate to a person, and keeps the record of why.

In development. Scroll to see a memory governed.

01 / Retain

Keep what has earned its place.

Every memory is written with its source, the conditions it applies under, a confidence score and a privacy class. Nothing enters the store without a reason the audit trail can show.

op=retain    aud_4q8r2m1c  rule=R7
ts       2026-11-02T09:14:02Z
subject  repo:atlas-api
memory   "API v2 ships behind flag billing_v2"
src      pr-review#4412  auth=maintainer
conf     0.91  class=internal  policy=default@3

02 / Update

Correct without erasing.

When a newer statement conflicts with an older one, Gromani checks authority and scope before it commits a lasting change, and is designed to leave what is still true alone. The old memory stays on the lineage, so you can see what was believed, and when.

op=update    aud_9x1k7d3p  rule=R5
ts       2026-11-02T09:16:40Z
subject  release:atlas-2.4
memory   "target 04-Dec" → "target 11-Dec"
src      standup-notes  auth=owner ≥ owner
lineage  supersedes=mem_7f21

03 / Forget

Forget on purpose.

Retention windows, privacy classes and deletion requests all remove memories. The fact goes. The audit entry that it existed, and was removed, stays.

op=forget    aud_2m6v8t0s  rule=R2
ts       2026-11-02T09:18:05Z
subject  incident:inc-2291
memory   mem_a9c4 "rate limit off on /export"
reason   retention-window elapsed 2026-10-15
audit    tombstone=kept

04 / Escalate

Know when to ask.

When the evidence is unclear, or a change matters too much to guess, Gromani asks a person instead of silently rewriting memory. The agent carries on with what it already knows, without acting on the disputed change, until someone decides.

op=escalate  aud_7c3n5w2e  rule=R4
ts       2026-11-02T09:21:33Z
subject  pricing:enterprise-tier
memory   "enterprise discount approved?"
src      agent-note  auth=inferred
conf     0.42 < 0.70  queue=review/product

Try a memory decision

Pick a statement. Watch the policy decide and write the entry.

An illustration: scripted scenarios against a seven-rule toy policy, not the Gromani engine. Statements, confidence scores and source labels are predefined here. Working those out from real project conversations is the hard part, and it is what we are building.

update

rule R5

Committed as a lasting change. The previous memory stays on the lineage.

Newer statement from owner supersedes mem_7f21 (owner, 2026-10-21). The old memory stays on the lineage.

“Release target 4 Dec” → “Release moves to 11 Dec after the load-test regression.”

Request

POST /v1/memories:propose{
  "subject": "release:atlas-2.4",
  "statement": "Release moves to 11 Dec after the load-test regression.",
  "source": {
    "channel": "standup-notes",
    "authority": "owner"
  },
  "confidence": 0.93,
  "class": "internal",
  "approved": true,
  "existing": "mem_7f21"
}

Audit entry

deciding…

Building agents that need to remember carefully?

Join the waitlist for early access. We are starting with agents for product development, operations and support, where a wrong memory costs something.

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