DocBrain ingests your scattered documentation — Confluence, GitHub, Slack, Jira — and turns it into an AI-powered knowledge system that answers questions with citations, learns from feedback, and tells you what's missing.
redis-cli -h payments-cache info memoryallkeys-lruCollects knowledge from everywhere your team works
Engineers waste 30-60 minutes a day searching for answers that exist somewhere. DocBrain fixes the three root causes.
Confluence, GitHub wikis, Notion, Google Docs, Slack threads, Jira comments. Knowledge lives in 7+ tools. Nobody knows where to look.
"How do I deploy to staging?" gets asked in Slack every week. Someone answers. Nobody writes it down. The cycle repeats.
340 of your 800 Confluence pages haven't been touched in a year. Nobody knows which ones are accurate until someone follows outdated steps at 2am.
How It Works
A four-phase pipeline that ingests, understands, answers, and learns — getting smarter with every question your team asks.
Point DocBrain at your Confluence spaces, GitHub repos, Slack channels, Jira projects. It chunks, embeds, and indexes everything — including images.
Hybrid search (vector + keyword) finds the right chunks. Cross-document references pull in linked Jira tickets, PRs, and runbooks automatically.
Grounded answers with citations, freshness badges, and confidence scores. No hallucination — every claim traces to a source document.
Every thumbs-up and thumbs-down trains the system. Procedural memory learns which docs answer which types of questions. It literally gets smarter.
4-Layer Memory System
Inspired by cognitive science. Four memory layers work together so every question makes the system sharper. The 100th query about Kubernetes is faster and better-answered than the first.
Cache hit rate
(mature deploy)
Avg response
time
Binary size
(Rust)
Multi-turn conversation context. Resolves "it", "that service", "the same thing" — so follow-up questions just work.
Every Q&A ever asked. Enables semantic caching (skip the LLM on repeat questions) and learning from feedback. The system gets cheaper as it learns.
Entities and relationships extracted from your docs. "Who owns the payment service?" resolved via graph traversal, not keyword matching.
Adapts retrieval strategy from feedback. Learns: "deployment questions → search DevOps space first." Not configured — discovered.
Autopilot
Most documentation tools serve what exists. DocBrain tells you what doesn't exist yet — by clustering low-confidence queries and negative feedback into actionable gaps.
Access Everywhere
One knowledge layer, five interfaces. Ask from Slack during an incident, from your IDE while coding, or from the terminal at 2am.
/docbrain ask
Dashboard + chat
docbrain ask
Cursor · Claude
Build anything
Features
Vector similarity + BM25 keyword in a single query. Catches both semantic meaning and exact matches like error codes and service names.
Every claim traces to a source document. No hallucination. Phantom citations are stripped. Trust what you read.
Every answer shows a freshness badge. Stale docs get flagged. Authors get notified when their high-traffic page is 14 months old.
Entities and relationships extracted from your docs. "Who owns the payment service?" resolves through graph traversal, not keyword guessing.
Slack thread links to a PR, PR references a Jira ticket, Jira points to a runbook. DocBrain follows the chain and enriches every answer.
OIDC, GitHub OAuth, GitLab OIDC. Three roles: viewer, editor, admin. Role mapping from IdP claims. API keys are Argon2-hashed.
Anthropic, AWS Bedrock, OpenAI, or Ollama (fully local). Swap LLM providers via config — zero code changes. No vendor lock-in.
Single 25MB static binary. Starts in <500ms. Under 100MB memory at load. Runs on 2 vCPUs. No Python virtualenv, no node_modules.
Your data never leaves your infrastructure. Docker Compose for dev, Helm chart for production Kubernetes. MIT licensed.
The Complete Loop
Every question is a signal. Every answer gets feedback. Every gap becomes a draft. Every draft becomes a doc. The loop closes automatically.
Next user gets the answer. Loop closed.
Docker, an API key, and three commands. That's it.