WikiFind
AI-powered search across your Notion, Confluence, and Google Docs.
● The Problem
Company knowledge is scattered across Notion, Confluence, Google Docs, Slack, and email. Employees spend 20% of their time looking for information. Native search in each tool only covers that one tool.
● The Solution
A unified search engine that indexes all your knowledge tools. Ask a question in natural language and get an answer with source links. "What is our refund policy?" returns the answer, not 30 documents to read.
Key Signals
MRR Potential
$20K-100K
Competition
High
Build Time
3-6 Months
Search Trend
rising
Market Timing
RAG (retrieval-augmented generation) made enterprise search actually work. Previous attempts at unified search failed because search quality was poor.
MVP Feature List
- 1Notion and Google Docs connectors
- 2Natural language question answering
- 3Source citation with links
- 4Slack bot interface
- 5Access control (respects source permissions)
Suggested Tech Stack
Build It with AI
Copy a prompt into your favorite AI code generator to start building WikiFind in minutes.
Replit Agent
Full-stack MVP app
Bolt.new
Next.js prototype
v0 by Vercel
Marketing landing page
Go-to-Market Strategy
Target companies with 50-500 employees using multiple knowledge tools. "Your team spends 8 hours/week searching for information" stat as the hook. Free trial for one workspace integration.
Target Audience
Monetization
Per-SeatCompetitive Landscape
Glean ($$$) and Guru target enterprise. Dashworks is mid-market. The "affordable for startups" lane using RAG technology is new and moving fast.
Why Now?
RAG technology makes this possible at a quality level that actually works. Previous enterprise search products failed because they returned documents, not answers.
Tools & Resources to Get Started
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