The models are ready. Your company's knowledge isn't.
That's the real blocker to AI automation now — not the models, but how your team actually works, scattered across docs, code and people's heads. RampBrain compiles it into governed skills an AI agent runs — refunds, incidents, approvals, access — every step sourced, gated on your approval, and sharper every time it's used.
Compiled skill · grounded in your sources
$533.33
§4
First three figures are widely-cited industry estimates (knowledge-management research).
Plugs into the tools your knowledge already lives in
The work stalls on what's in people's heads.
Your team already knows how to handle it. But every decision routes through the one person who remembers the rule — and AI that only answers can't pick up the slack.
"Ask Raj, he knows."
The refund edge case, the deploy quirk, who signs off on what — it lives in one person's head. When they're out, the work waits.
"Is this within policy?"
Every borderline refund, discount, or access request pings the one person who knows the rule. The policy exists — in a doc nobody opens — so the same call gets re-made by hand, all day.
"The runbook's out of date."
An incident hits at 2am. The runbook was written once and never updated, so on-call guesses — instead of following what actually fixed it last time.
"The AI can answer. It can't act."
A chatbot surfaces a document and stops. It won't safely run your refund or incident process — because it doesn't know your rules, and nobody trusts it to act without a gate.
Every team has a Raj.
Raj knows which refunds to approve. Raj knows what actually fixed the last outage. Raj knows how things really work around here — and none of it is written down.
Raj is one two-week notice away
from taking all of it with him.
You don't get three features. You get a compiler.
Point RampBrain at any operating policy and it compiles a governed workflow — with that policy's own decision options and limits. Refunds and incidents ship as showcases; everything else, you compile yourself. No new module, no engineering.
Not a doc-search tool. A loop that compounds.
Compile how your team operates into skills an agent runs — safely — and that get sharper every time they're used.
Ingest & understand
Connect your sources. We parse and structure them into a living map of how your team operates — processes, rules, ownership, decisions.
Compile a skill
Any policy becomes a grounded skill — its decision options, limits, steps and guardrails, each traced to a source, and the gaps flagged.
Agent proposes, you approve
The agent acts on documented rules only and escalates on a gap. You approve — then it runs the safe step; money and prod changes stay a cited human checklist.
Learns from the resolution
Capture how a case was resolved and RampBrain recompiles the skill in place — closing the gap that caused the escalation. Next time, it just handles it.
A real decision — grounded, and gated.
On a live request the agent matches a documented rule, proposes the call — and stops at your guardrail. The irreversible step always stays a human one. Same primitive, any workflow:
$533.33refund-policy.md §4→ Hit a gap in the policy and the agent escalates instead of guessing — and issuing the refund always stays a human step.
≤ 15% auto-approve at rep leveldeal-desk.md §2→ Same engine as refunds — but this workflow has its own decisions (approve · escalate · deny) and its own 15% limit, both read from your policy.
read-write → requires security owner approvalaccess-policy.md §4→ The agent drafts the Linear issue and assigns the owner — but granting the access stays a human decision.
A brain that gets sharper every time.
Most tools are as good on day 100 as day one. RampBrain isn't. Every time your team resolves a case the agent escalated, that resolution becomes part of the brain.
- 1The agent hits a gap in your policy and escalates instead of guessing.
- 2A human resolves it and captures how — one note, a few checkboxes.
- 3RampBrain stores it as a sourced document and recompiles the skill in place.
- 4The gap is closed. Next time that case comes in, the agent just handles it.
The work gets more consistent, and the brain more valuable — exactly the asset that's hard for a competitor to copy, because it's built from your resolutions.
The agent does the safe work itself.
Once you approve, RampBrain takes the coordinating action — so the decision turns into motion, not another task on someone's list. The irreversible steps stay yours.
Posts to Slack
Fans out a grounded heads-up to the right channel — the matched rule, the proposed call, and the source — so the team sees it where they already work.
Safe · still gatedOpens a Linear / GitHub issue
Drafts the issue with the owner, context and citations attached — the escalation becomes a tracked ticket the moment you say go.
Safe · still gatedCalls your webhook
Fires a clean payload to your URL — n8n, Zapier, your own automation. We store no third-party secrets; the action posts only where you point it.
Safe · still gatedMoney moves and production changes never auto-run. They stay a cited human checklist with a hard gate in code — an action that needs approval and hasn't got it is blocked before it can touch anything.
Not a chatbot. A system that does the work.
Everyone can build RAG over documents. Our moat is two layers deeper — and it compounds.
We don't just answer. We compile your knowledge into skills an agent runs.
Any policy becomes a grounded SKILL.md — decisions, steps and guardrails, each traced to a source — that an AI agent loads over MCP and actually executes. Q&A is table stakes; doing the work is the product.
It acts only on your rules, never without sign-off — and it learns.
It works from documented rules only and escalates on a gap. With your approval it runs the safe coordination; money and production stay a human checklist. And every resolution you capture feeds back into the brain — so it's sharper next week than it is today.
An agent you can actually trust to act.
Letting AI do real work only works if it can't go off-script. Your knowledge stays yours, and nothing the agent proposes runs without you.
Encrypted & isolated
Everything moves over encrypted (HTTPS) connections, and any connector tokens are encrypted at rest. Each workspace is fully isolated — your knowledge is never mixed with another company's.
Human-gated, nothing auto-runs
Every action waits for one-click approval. Dry-run actions simulate safely; outward actions (Slack, Linear, your webhook) only fire on your go — and money or production steps are hard-blocked in code without it.
Yours, never sold
We never sell your data or share it for advertising. You choose what gets ingested and can delete any document, source, or your entire workspace at any time. Delete it, and it's gone.
Real work, run from your own playbook.
The operational calls your team makes from memory every day. RampBrain runs them from your documented rules — sourced, gap-aware, and waiting on your approval.
A customer wants a $640 refund — is it within policy?
The payment service is down at 2am — what fixed it last time?
Sales wants a 22% discount — who signs off, and is it allowed?
Someone needs prod database access — grant it or escalate?
This case hits an edge the policy doesn't cover — escalate, don't guess.
A new engineer starts Monday — draft the day-one plan, then wait for me.
Start free. Upgrade when agents do more.
Free to compile your first skills. Go Pro for unlimited workflows, every connector, and agents that run the work end-to-end.
- 1 connected source
- 3 skill runs / month
- Knowledge map & Ask
- Tribal-knowledge capture
- Community support
- Unlimited sources & docs*
- Unlimited workflows & agent actions*
- All connectors — Slack, Jira, Notion, Linear, Confluence
- Outward actions: Slack, Linear, GitHub, webhook
- Self-updating flywheel + daily auto-refresh
- Skills export + MCP server · priority support
- Dedicated AI quota / your own keys
- SSO & role-based access
- Self-host option
- Security review & SLA
- Dedicated support
* Unlimited under fair use — generous limits sized for normal team usage, not automated bulk runs.
The biggest blocker to AI automation is no longer the models. Now the blocker is the domain knowledge. Every company in the world is going to need a company brain.Tom Blomfield — Y Combinator, Request for Startups
I'm Jay, a final-year CS student. I kept seeing the same thing — the knowledge that actually runs a team lives in a few people's heads, so every refund, every incident, every approval waits on whoever remembers the rule. RampBrain is my attempt to fix that: turn what your team already knows into skills an AI agent can actually do the work with — safely, always under your sign-off, and getting sharper every time. I'm building it in the open, and I read every piece of feedback personally.
Questions, answered.
How is this different from ChatGPT or a doc search?
ChatGPT and search surface a document — they don't do the work. RampBrain compiles your knowledge into grounded, governed skills an agent runs: it acts only on documented rules, refuses to guess (it escalates) when a request hits a gap, traces every step to a source, and stops for human approval before anything executes.
What kinds of work can it run?
Any operational decision your team makes from a policy — refunds, incident response, discount and deal-desk approvals, access requests, spend sign-off, vendor review, onboarding. You don't get a fixed list of features: you point RampBrain at a policy doc and it compiles a workflow with that policy's own decision options and limits.
Is it safe to let an AI handle refunds and incidents?
Yes — by design. The agent only acts on rules documented in your sources, escalates instead of guessing on a gap, and every action waits for one-click approval. Money decisions and production-mutating steps stay a cited human checklist, never auto-run. More in Security & trust.
Does it get better over time?
Yes. When a case is resolved, you capture how — RampBrain stores that as a sourced document, recompiles the skill in place, and closes the gap that caused the escalation. The brain gets sharper the more your team uses it.
What can I connect?
GitHub repositories, documents (PDF, Markdown, code files), Slack exports, Jira, Confluence, Notion, Linear — plus 5-minute knowledge interviews. And outward: the agent can post to Slack, open a Linear or GitHub issue, or call your own webhook.
Who is it for?
Teams that run the same operational decisions from memory — support handling refunds, on-call responding to incidents, ops approving discounts and access — and want them done consistently, sourced, and safely.
Put your company's
playbook to work.
It's live and free — connect a repo, compile your first skill, and watch an agent propose its first action. You approve.
Or get product updates: