A ATRIUM
Series A · Confidential · 2026
Governed decision memory

The institutional memory layer for humans and AI.

Atrium captures the decisions a company makes — the why, the evidence, the dissent — and serves them as governed context to every employee and every AI system that works alongside them.

StageSeries A
SectorAI Infrastructure · Knowledge
WedgeProduct & engineering memory
Contactfounders@atrium.co
ATRIUM02 / The Problem
StatusDecisions disappear
The problem

Companies are losing the why behind every decision.

01 — Scattered

Knowledge lives in twelve places at once.

Slack, Zoom, Notion, Jira, Linear, dashboards, tickets — and the heads of the people who were in the room.

02 — Stale

Rationale rots faster than content.

Decisions get made, then re-debated months later because nobody can find what was decided or why.

03 — Lost

Memory walks out the door.

Every departure takes uncodified context with it. AI agents inherit the same picture.

Channel#eng-platform
DocQ3 Roadmap (v17)
DocQ3 Roadmap (v8) ↩
MeetingArch review · Apr 2
TicketJIRA-4471
Thread#incidents (deleted)
PRDBilling rewrite
DMMaya → Sami
WikiAuth (2024)
EmailRe: vendor
Atrium · Confidential02
ATRIUM03 / Why now
Forcing functionAI in core workflows
Why now

AI just made institutional memory a system-of-record problem.

Agents are entering the workflows where decisions get made. They need context that is current, authoritative, and inspectable — and the existing knowledge stack cannot provide it.

Agents in production
3.4×
Increase in AI agents deployed in enterprise workflows over the last 18 months. They retrieve company context on every turn.
Trust gap
71%
Of enterprise AI leaders say lack of governed organizational context is the top blocker to deploying agents in production.
Knowledge debt
$42B
Annual productivity loss from re-finding, re-deciding, and onboarding around lost institutional knowledge.

Existing wikis, search, and RAG pipelines were built for documents. None of them establish authority, model disagreement, or expose change over time — the things AI systems actually need.

Sources: Atrium customer interviews (n=42), Menlo State of AI 2025 — directional03
ATRIUM04 / Core insight
ReframeDecisions, not documents
Core insight
What we used to think

Knowledge = documents.

If you can find the right doc, you have the answer. Search, wikis, and RAG all assume this.

What's actually true

Knowledge = decisions.

The doc is a snapshot. The valuable artifact is the decision behind it: who chose what, on what evidence, with what dissent, and what came before.

Companies don't lose documents. They lose decisions — the why, the dissent, and what was true last quarter.

A decision is
A choice with provenance
It carries
Evidence & rationale
It admits
Dissent & uncertainty
It changes
Over time, on the record
Atrium · Confidential04
ATRIUM05 / Landscape
CategoryNew: governed memory
Existing solutions fall short

Today's tools retrieve content but can't establish authority.

Every category in the knowledge stack indexes what was written. None of them model what was decided, by whom, or whether it still holds.

Category Authority Disagreement Provenance Change over time
Enterprise search
Glean, Coveo
Returns hits, not truth Not modeled Source-of-doc only Latest doc wins
Wikis
Notion, Confluence
Manual upkeep Comments, not structure Author, not evidence Page history, no semantics
RAG / copilots
Vector retrieval
Retrieves stale & disputed Conflates contradictions Chunks lose context No supersession
Knowledge graphs
Custom / opaque
Hard to inspect Single-truth model Edges, not evidence Brittle to change
Atrium
Governed decision memory
Validated by named owners First-class dissent Evidence + rationale per claim Supersession on the record
Atrium · Confidential05
ATRIUM06 / Product vision
LayerSystem of record
Product vision

A governed memory layer for organizational truth.

Atrium captures what the company believes, why, and based on what — then exposes it as trusted context to every human and every AI agent that needs it.

  • 01Capture decisions, not just documents
  • 02Preserve rationale, evidence, and dissent
  • 03Govern through human validation and audit
  • 04Serve via API, skills, and fine-tunes
SYSTEM SCHEMATIC · v0.4 ATRIUM/CORE
InputsSlack threads
InputsMeeting transcripts
InputsPRDs · tickets
InputsDashboards · metrics
— Atrium core —

Governed Decision Memory

extract → validate → record →
contradict → supersede → serve
Owner
Named
Status
Tracked
Provenance
Required
Dissent
First-class
ConsumersHuman reviewers
ConsumersAI agents (API)
ConsumersSkills / tools
ConsumersFine-tune corpora
Permission-aware Auditable Inspectable Version-tracked
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ATRIUM07 / How it works
FlowSignal → Validated decision
Example workflow

From signal to validated decision in four steps.

Atrium runs continuously across your communication and work surfaces. Every step is inspectable; nothing becomes "official" without a human in the loop.

01 · INGEST

Watch where decisions actually happen.

Permission-aware connectors stream Slack, Zoom transcripts, Notion, Linear, GitHub, dashboards, and tickets — without copying them.

Signal slack/#eng-platform
"let's go with kafka over kinesis — cheaper at our volume."
02 · EXTRACT

Surface a candidate decision.

Models propose a structured decision: claim, owner, rationale, evidence, confidence. Routed to the named owner — never auto-published.

Candidate DEC-1419
"Use Kafka for event bus."
owner: @maya · conf: 0.71
03 · VALIDATE

Owner approves, edits, or rejects.

One-click confirmation with attached evidence. Owners can mark disputed, request review, or supersede a prior decision on the record.

Action @maya · approved
+rationale, +2 evidence,
supersedes DEC-0922
04 · SERVE

Available to humans and AI.

Validated decisions are queryable via API, embedded in skills, and used to fine-tune. Stale and contradicted claims surface automatically.

Consumers api · skills · ft
agents.query("event bus")
→ DEC-1419, current, conf 0.95
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ATRIUM08 / The product
ViewLive · INC-2207
The product · live decision

Memory tracks decisions while they're being made — not just after.

Workspace
All decisions 2,847
Mine to validate 7
Live · in-flight 3
Stale 31
Domains
Architecture 412
Platform / Infra 186
Incidents 221
Roadmap 94
In-flight now
INC-2207 · Cassandra live
DEC-1419 · Kafka mig 62%
DEC-1388 · Webhook v1 disp
Incidents · Cassandra · INC-2207

Cassandra cluster eu-west-1 — degraded reads, paging customers.

Live · 47 min Incident commander: @sami Sev-2 · customer-impacting 3 active contributors
Working hypothesis (auto-tracked)

Compaction backlog on node-04 starving read replicas. Failover to eu-west-2 rejected at 12:41 — billing RTT too high. Current path: rolling restart + read quorum reduction.

Live progress · captured from signals
Resolution metrics · refreshed 8s ago
p99 read latency↓ 64%
Error rate↓ 81%
Customers paged12 → 4
Compaction queuedraining
Live evidence stream
+47:12datadog@sami — p99 returning to baseline.
+38:04claude code@dani corrected agent on nodetool repair sequencing.
+24:50slack@maya — "node-04 first, learned this Q1."
StatusResolving
Time open47m 12s
Customers12 affected · 4 paged
Confidence in fix0.78
Related decisions3 linked
Linked institutional memory
Q1·24Cassandra upgrade runbook — node-04-first ordering applied
2023Failover to eu-west-2 — RTT cost analysis cited
DEC-1290OpenTelemetry adoption — fueling these metrics
Live consumers
Skillincident-co-pilot · Claude Code · 7 calls
Skillaws-cli-our-way · learned from @dani's correction
APIStatuspage auto-pulls customer impact
Will become
Postmortem skeleton (auto)
Runbook patch · @dani validates
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ATRIUM09 / Wedge
BeachheadProduct & engineering
Initial wedge

We start with product and engineering decision memory.

It's where the highest-stakes decisions are made, where the cost of forgetting compounds fastest, and where AI tools have the deepest reach. Land here, expand horizontally.

  • CAPTUREArchitecture decisions, roadmap tradeoffs, incidents
  • REDUCERepeated debates and onboarding friction
  • UNLOCKAI coding agents that know your real choices
  • EXPANDGTM, finance, legal — once memory is the habit
Live decision board · Platform / Infra
DEC-1419 · CURRENT Use Kafka for event bus
@mayaconf 0.95
DEC-1402 · CURRENT Read replicas in eu-west-1
@samiconf 0.92
DEC-1388 · DISPUTED Deprecate webhook v1 by Q3
@priya2 dissenting
DEC-1351 · CURRENT Single auth service for B2B + B2C
@rohanconf 0.88
DEC-0922 · SUPERSEDED Use Kinesis for event bus
2024by DEC-1419
DEC-1290 · CURRENT Adopt OpenTelemetry org-wide
@daniconf 0.91
Atrium · Confidential09
ATRIUM10 / Buyer & user
GTMTop-down + bottoms-up
Who buys, who uses

Sold to platform leaders, used by the people closest to the decisions.

A budget conversation with one VP unlocks daily use across the engineering and product org.

01 — Buyer

VP Product, CTO, Head of Product Ops, AI Platform Lead.

  • Owns the AI agent rollout
  • Accountable for org-wide alignment
  • Holds budget for knowledge & platform
  • Pain: AI answers can't be trusted
TriggerFirst agent in production failed an exec demo on stale context.
02 — User

Staff engineers, PMs, TPMs, EMs, chiefs of staff.

  • Validate decisions in their domain
  • Search for prior rationale daily
  • Onboard the next person joining
  • Value: stop re-litigating the same call
TriggerThird time this quarter someone asked "didn't we already decide this?"
03 — ICP

Fast-growing B2B software companies, 300–3,000 employees.

  • Heavy Slack + Notion + Jira footprint
  • Active AI / agent adoption
  • Multiple product lines or business units
  • Compliance-aware (SOC2 / ISO)
ProfileThe company AI agents will materially shape inside 24 months.
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ATRIUM11 / Trust & governance
PosturePermission-aware by default
Trust & governance

Trust is the product — governance is built into ingestion and serving.

A memory layer that AI systems rely on must be auditable end-to-end. Five guarantees, written into the data model.

01

Permission-aware

Ingestion and serving respect source-system ACLs. A decision is only visible to viewers who can see all of its evidence.

acl ⨯ row-level
02

Human-validated

Nothing becomes "official" without a named owner clicking approve. AI proposes; humans decide.

@owner · approved
03

Provenance-required

Every claim cites its evidence — Slack threads, transcripts, dashboards — and links back to the source.

claim → evidence[]
04

Audit-traced

Edits, supersession, and review cycles are logged and replayable. Compliance gets a clean export.

diff · who · when
05

Uncertainty-aware

Disagreement, confidence, and review status are first-class. Stale or disputed decisions surface, never silently disappear.

conf · dissent · stale
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ATRIUM12 / Closing
RoundSeries A · raising
The opportunity

The future company memory
is governed, inspectable,
and AI-readable.
We're building it — and we want to be the system of record for organizational truth.

Raising
Series A · $14M
Use of funds
Eng (12), GTM founding team, design partners
Traction signal
6 design partners, 3 paid, $480k ARR booked
Contact
founders@atrium.co
Atrium · Confidential12