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The Company Brain That Doesn’t Degrade

Make employees and agents know your company’s ins and outs like your most tenured engineer.

Run the demoInside your cloud

Built on 120+ deep dives with tech leads from

  • bBumble
  • Angular
  • JPJPMorgan
  • Notion
  • Datadog
  • RRamp
  • Stripe
  • Figma
  • Vercel
  • Shopify
  • Atlassian
  • Twilio
  • Snowflake
  • HubSpot
  • Airbnb
  • Uber
  • Spotify
  • Slack
  • Netflix
  • Salesforce
  • Adobe
  • Nvidia
  • Tesla
  • GitHub
  • Reddit
  • Dropbox
  • Zoom
  • PayPal
  • Coinbase
  • DoorDash
  • Discord
  • OpenAI
  • Cloudflare
  • MongoDB
  • Databricks
  • LinkedIn
  • Klarna
  • Revolut
  • Google
  • Amazon
  • Meta
  • Apple

Capture, at the physical layer

LIVE
mayalet’s ship the EU cluster on Friday
omaronly after the residency check, remember Berlin
CLAUDE CODE
you> add the residency check to the deploy runbook
claudedone, runbook updatedsaved to the brain
you> ship the EU cluster once it passes

Structured into agent memory

A knowledge graph with 10 dimensions of structure, designed from 120+ interviews with tech leads.

Core purposeCustomer data stays in region
North star / KPIsExport success rate
Strategy & goalsEU expansion, Q3
RoadmapEU cluster GA
DecisionsEU data residency gate
PeopleBerlin incident, Omar
Processes / SOPsDeploy runbook
ImplementationResidency check step
Projects & systemsEU cluster
ImpactQuarter-end exports

Answer, everywhere

Connect once. Each meeting and session it sits in makes the next answer sharper, with the source attached.

OVER MCP
Claude CodeCursorCodex
What breaks if we change the ingestion schema?
Search and analytics consume it directly; patch the digest lambda first
DESIGN MEETING · LIVE
lenawhy do exports fail every quarter-end?
omarcentralagent, thoughts?
centralagentAcme batch-uploads on the 30th; exports need the widened queue pool from the Q1 incident fix

Frontier agents are like smart consultants. With CentralAgent they work like your most tenured engineer.

Ask like you’d ask your most tenured engineer

What you have to write into each session

❯ We reach brain A, brain B and brain C through the CentralAgent MCP. The MCP default, the portal ask-all path and the meeting bot each behave differently, so check the server defaults, the portal tests and the eval notes. Then tell me which brains we should query by default, and why.

What you ask when CentralAgent is connected

❯ Which brains should we query by default, and why?

Same task, two sessions

Without CentralAgentgranolaawsgithubnotionready
❯ Which read path should consumers use by default, and why?

answer

A mid-level engineer’s answer31 tool calls · 3:33
With CentralAgentgranolaawsgithubnotionready
❯ Which read path should consumers use by default, and why?

answer

A principal engineer’s answer6 tool calls · 41s
you

Which read path should consumers use by default, and why?

Without CentralAgentWith CentralAgent

All inside your cloud

CentralView ships with your CentralAgent: sources feed in on the left, three brains structure what they capture into one company brain, and the MCP endpoint serves every harness you connect. It runs in your private cloud, under your control.

CentralViewdrag sideways or with two fingers to move the mapTry it yourself
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AI runs on context

Models improve for everyone. Only yours gets smarter about your company.

Frontier models train on the public internet; your decisions, constraints, and hard-won fixes are not in it. CentralAgent briefs the agents you already run, over MCP, and every agent you connect starts smarter.

Intelligence plus tribal knowledge is what your most tenured engineer runs on.

Start collecting your tribal knowledge

Deployed in your VPC. Even the CentralAgent team can’t access your data.
Book your setup call
  1. Day 1One setup call, then our engineer deploys the brain inside your VPC.
  2. Week 1Your meetings and agent sessions start flowing in.
  3. Week 2First answers that used to need a veteran: why a decision was made, which fix actually worked, who owns what. Each one cites the meeting or session it came from.
  4. Day 30Questions that used to wait on a Slack thread come back in seconds, with sources. Your coding agents pull the same answers over MCP.

Questions

How is this different from other company brains?
Tech leads in our 120+ interviews kept describing the same arc: a generic knowledge store works for a month or two, then retrieval degrades as content piles up. So we modeled CentralAgent’s memory on how biological memory consolidates, with per-role structure. In our testing it held up as content grew, where the generic store’s retrieval degraded. Comparisons: vs Glean, vs Notion AI.
What is CentralAgent?
The company brain that doesn’t degrade. CentralAgent captures the knowledge your most tenured people carry in their heads, structures it into layered agentic memory inside your private cloud, and lets every employee and every agent inherit it. Capture starts in your meetings and agent sessions, where most of it sits. See how it works.
Who is CentralAgent for?
Teams that want employees and AI agents to know the company’s ins and outs like their most tenured engineer, including the coding agents they already run (Claude Code, Cursor, Codex). It starts from one setup call.
Where does our data live?
In your private cloud, start to finish. It never leaves and nobody trains on it. Details on the security page.
Does it work with Claude Code, Cursor, and Codex?
Yes. The brain is one MCP endpoint, so any agent that speaks MCP can use it. Teammates query the same memory in CentralView.
How is this different from Granola?
Different jobs. Granola takes meeting notes, per person who runs it. CentralAgent sets up once for the whole company and captures continuously: meetings and agent sessions both, mapped into one memory the way a principal engineer thinks, so the note from a design review links to the session that fixed the deploy it discussed.
We already keep a CLAUDE.md. Why this?
Keep it. A rules file holds what someone remembered to write, per repo, and it goes stale. CentralAgent updates itself from every meeting and agent session, spans repos and teams, and answers questions no rules file anticipated.
Where in our development lifecycle does this plug in?
Wherever your agents work. The brain is one MCP endpoint, so any phase where an agent needs company context can draw on it: writing specs against past decisions, reviewing designs, planning tests around known failure modes.
How should a 30-person startup choose a company brain?
Check three things: whether retrieval holds up as content grows, how it is priced, and where your data lives. CentralAgent is built to hold up, and it has no seats and no subscription, so there is no seat minimum to clear at 30 people: you pay the model’s published per-token rate plus 30% for what the brain reads and answers. The servers run in your cloud, on your own bill. See pricing.
What is tribal knowledge?
The knowledge that lives only in people’s heads: how things really get done, why decisions were made, what never to do. More on the tribal knowledge page.
How do I capture tribal knowledge from senior engineers before they leave?
Capture starts where it already gets said: in meetings and in the agent sessions where they work, and it reads the tools you already use. Nobody writes a doc, and nobody changes how they work. Day 1: One setup call, then our engineer deploys the brain inside your VPC. Week 1: Your meetings and agent sessions start flowing in. Week 2: First answers that used to need a veteran: why a decision was made, which fix actually worked, who owns what. Each one cites the meeting or session it came from. More on where tribal knowledge hides.
What tools help onboard new engineers faster with AI?
Once the brain is running, a new hire or a fresh agent session starts with your company’s context already loaded. Thirty days after setup: Questions that used to wait on a Slack thread come back in seconds, with sources. Your coding agents pull the same answers over MCP.