Your Docs. Finally Useful.
Your team asks the same questions 50 times a week. AI answers in seconds using your own documents. Support tickets drop. Onboarding accelerates.
Good Info. Bad Access.
The problem
The answers exist. They are in Notion, Google Drive, Confluence, someone's head. But finding them? That is the problem.
- • New hires take 3 months to stop asking basic questions
- • Support answers the same question for the 50th time
- • Senior people become question-answering machines
- • When people quit, knowledge walks out the door
What RAG does
AI reads your docs. User asks question. AI finds answer and cites the source. Instant. Accurate. Verifiable.
- • Answers in seconds, not hours
- • Every answer links to source
- • Works 24/7, never gets tired
- • Scales without headcount
Pick Your Use Case
Internal Knowledge Base
Stop repeating yourself
Team asks question. AI searches your docs. Answer appears. Your experts stop being help desks.
- Search Notion, Confluence, Google Docs
- Policy and procedure Q&A
- Technical documentation search
- Onboarding assistant
- Slack/Teams integration
Customer Support Agent
70% fewer tickets
Customer asks question. AI checks your help docs. Answer delivered instantly. Complex issues escalate to humans.
- Help center integration
- Product documentation search
- Account-specific answers
- Human handoff for complex issues
- Multi-language support
Document Processing
10x faster review
Contracts, invoices, research papers. AI reads them, extracts what matters, flags issues. Humans review. Not do the grunt work.
- Extract structured data from PDFs
- Contract analysis and comparison
- Invoice processing
- Research paper summarization
- Compliance document review
How RAG Works
Index
Your documents are chunked and converted to vectors that capture meaning
Query
User asks a question in natural language
Retrieve
System finds the most relevant document chunks
Generate
AI creates an answer from retrieved content with citations
The key insight: RAG grounds AI responses in your actual documents, dramatically reducing hallucination.
Implementation Process
Discovery & Architecture
- Document source audit and access setup
- Use case prioritization and scope definition
- Architecture design (cloud vs self-hosted)
- Integration requirements mapping
Core Build
- Document ingestion and preprocessing
- Vector database setup and indexing
- Retrieval pipeline configuration
- Initial prompt engineering
Refinement & Testing
- Accuracy testing with real queries
- Retrieval tuning (chunk size, overlap, reranking)
- Response quality optimization
- Edge case handling
Integration & Launch
- UI/chat interface deployment
- System integrations (Slack, Teams, etc.)
- User training and documentation
- Monitoring and analytics setup
Pricing
Starter
Single use case, limited docs
- Up to 1,000 documents
- 1 data source integration
- Web chat interface
- Basic analytics
Professional
Production-ready system
- Up to 10,000 documents
- 3-5 data source integrations
- Slack/Teams integration
- Advanced analytics & feedback
- Priority support
Enterprise
Self-hosted, full customization
- Unlimited documents
- Self-hosted deployment
- Custom integrations
- Role-based access control
- SLA guarantees
Technology We Use
Frequently Asked Questions
What documents can it read?
PDFs, Word, spreadsheets, Notion, Confluence, Google Docs, emails, Slack. If it has text, we can index it. Scanned docs too, via OCR.
Does it make stuff up?
No. RAG cites sources. Every answer links back to the document it came from. When it does not know, it says so instead of guessing. Typical accuracy is 85-95%.
Is our data safe?
Yes. Self-hosted option available. Enterprise cloud with SOC 2. Your data never trains models. Role-based access means people only see what they should see.
What happens when it cannot answer?
It says 'I do not know' and offers to escalate. No hallucinations. Unanswered questions get logged so you know what docs to add.
How long to build?
Basic internal knowledge base: 2-4 weeks. Customer support agent: 4-8 weeks. Enterprise with custom integrations: 8-12 weeks.
See It In Action
Make Your Docs Work
30 minutes. We look at your docs, your use case, and tell you what is realistic.
Book the Call