Internal knowledge base
Stop paying senior engineers to answer the same five questions.
Every mid-size engineering org has the same leak: the two or three people who know how things actually work spend a quarter of their week answering DMs, explaining the same patterns, pointing new hires at the same runbooks. That's not a training problem. That's a knowledge problem — and it has a real fix.
The pattern
You already have the answers. They're scattered across Confluence, Google Docs, Notion, Slack threads, closed pull requests, Jira comments, and the heads of your senior engineers. When a new engineer has a question, they ask a person because asking the docs is slower and less reliable than asking a human — and the person usually knows something the docs don't.
A well-built internal knowledge base with an AI interface flips that economics. Asking the docs becomes faster and more reliable than asking a human, and the human interventions get captured and fed back into the system every time they happen.
What we build
Ingest pipeline
We index your Confluence, Google Docs, Notion, SharePoint, Jira, GitHub, Slack channels, and any custom systems. Incremental updates, respect-your-ACLs permissioning, deduplication across duplicate source docs.
Hybrid retrieval
Vector search plus BM25 plus rerankers, tuned against a small eval set from your actual team's questions. Not the default LangChain template — a real retrieval pipeline that handles the awkward long-tail of your org's vocabulary.
AI chat interface
Plugged into the private internal LLM platform (or as a standalone chat). Answers grounded in your docs with inline citations, so engineers can jump to the source. No made-up citations — if the system doesn't know, it says so.
Slack / Teams bot
Ask questions in the channel where the old questions used to get asked. The bot answers from the knowledge base first; if it doesn't know, it posts the question to your experts with context already attached.
Feedback loop
Every answer is rated (thumbs up / down) and every correction gets captured. Weekly we surface the questions the system answered poorly, so your experts can write one good doc that teaches the system forever.
Governance and privacy
Every source is tagged with its data classification. Restricted docs are only surfaced to users with the right role. Full audit log of every query, who asked it, and which sources were returned. SOC 2 and privacy-review ready.
What typically gets measured after 90 days
- Senior engineer time spent answering DMs drops by 40–70%.
- New hire onboarding time drops by 1–3 weeks.
- "Where is the doc for X?" becomes a self-serve answer.
- The docs themselves get better — because every gap the system exposes gets fixed.
We don't promise these numbers in a pitch. We measure them honestly, on your cohort, and give you a report that you can show leadership.
Combine with training for the full effect
A knowledge base answers the repeatable questions. Training handles the non-repeatable ones. Bundled together, your senior engineers get their best hours back, new hires ramp faster, and your tooling adoption actually sticks.