eazyware
Use case

RAG knowledge base for internal teams

Instant semantic search across all your internal docs, tickets, and tribal knowledge.

Overview

An enterprise knowledge assistant that ingests your Notion, Confluence, Slack, Linear, and Google Drive — then lets employees ask questions in natural language with cited sources. Keeps current via scheduled reindexing.

Key questions we answer during scoping
  • How do we handle permissions and document-level access?
  • Which sources add signal vs. noise?
  • How do we keep embeddings fresh as sources change?
  • How do we prove ROI beyond "feels faster"?
Reference timeline
6–8 weeks
Investment
$60k–110k
Best for
  • 500+ employees
  • Distributed knowledge (multiple tools)
  • High onboarding cost
Typical outcomes

What shipping this looks like.

94%
answer relevance
4.2M
docs indexed
<2s
time-to-answer
Reference stack

The typical tools for this use case.

Every engagement picks the right tool for your context — these are defaults, not prescriptions.

Pinecone / pgvectorOpenAI embeddingsLangChainCohere rerankerHybrid search
/ Next step

Thinking about rag knowledge base for internal teams?

Book a 30-minute scoping call. We'll tell you what shipping this looks like for your context.

~4h
avg response
Q2 '26
next slot
100%
NDA on request