PRD — Knowforge
Product Name
Knowforge
One-Line Description
Knowforge helps startups and small businesses turn scattered documentation into searchable, AI-chat-enabled knowledge bases in minutes.
Executive Summary
Knowforge is a multi-tenant SaaS platform that allows organizations to upload existing documentation and instantly transform it into an organized knowledge base powered by Retrieval-Augmented Generation (RAG).
Users can upload files such as PDFs, DOCX, Markdown, text files, and internal documentation. Knowforge automatically processes content, structures information, enables semantic search, and provides an AI chat assistant capable of answering questions using trusted company sources.
The platform is designed around speed, simplicity, tenant isolation, and scalable infrastructure.
Problem Statement
Most growing teams already have valuable knowledge, but it is fragmented across:
- PDFs
- Docs
- Notion pages
- Wikis
- SOPs
- Support files
- Product manuals
- Internal notes
- Policy documents
This causes:
- Slow access to information
- Poor onboarding
- Repetitive support questions
- Lost productivity
- Inconsistent answers
- Outdated documentation systems
Core Value Proposition
Upload your files today.
Get a searchable and chat-enabled knowledge base in minutes.
Primary Goals
- Make knowledge instantly accessible
- Improve onboarding speed
- Reduce repetitive support questions
- Enable AI chat over trusted documentation
- Deliver fast workspace setup
- Support multiple organizations securely
Secondary Goals
- Improve internal search
- Surface documentation gaps
- Measure knowledge usage
- Enable public support portals
Non Goals (MVP)
- Enterprise SSO
- Fine-tuned custom LLMs
- Complex workflow approvals
- Advanced OCR for scanned documents
- Billing automation
- Multi-language translation engine
- CMS-grade editorial tooling
Target Users
Primary ICP
- Startups
- Small ecommerce businesses
- Small operations teams
- Growing companies with scattered docs
User Roles
Owner
Workspace owner managing users and settings.
Admin
Manages content, analytics, permissions.
Editor
Uploads and updates documentation.
Viewer
Consumes internal knowledge.
External User
Uses public KB or support chat.
Key Use Cases
Startup Onboarding
Upload SOPs, policies, team docs.
Ask:
How do we deploy production changes?
Ecommerce Support
Upload shipping, returns, warranty docs.
Ask:
How long do refunds take?
Product Documentation
Upload manuals and guides.
Ask:
How do I reset the device?
Internal Search
Ask:
Where is our vacation policy?
Product Principles
- Fast setup over heavy configuration
- Source-grounded answers over hallucinations
- Simplicity over feature bloat
- Secure tenant isolation by default
- Strong developer-grade architecture
Functional Requirements
1. Authentication
- Register/login
- JWT sessions
- Role-based access control
- Workspace invitations
2. Multi-Tenant Workspaces
- Create organizations
- Unique tenant slug
- Tenant-isolated data
- Separate usage tracking
3. Document Management
Supported formats:
- PDF
- DOCX
- TXT
- Markdown
- CSV
- URLs (future)
Features:
- Upload files
- Delete/archive files
- View indexing status
- Metadata management
4. Automatic Knowledge Structuring
AI-assisted:
- Category suggestions
- Titles cleanup
- Summaries
- Tags
- Related documents
Human override allowed.
5. Ingestion Pipeline
When files are uploaded:
- Store raw file
- Extract text
- Normalize content
- Chunk intelligently
- Generate embeddings
- Index vectors
- Update status
6. Semantic Search
- Natural language search
- Ranked relevance results
- Tenant-filtered retrieval
7. AI Chat (RAG)
- Ask questions in plain language
- Retrieve relevant chunks
- Generate source-backed answers
- Show citations
- Admit uncertainty when context is insufficient
8. Knowledge Base Portal
- Public/private access
- Category browsing
- Search
- Read documents
9. Analytics Dashboard
Track:
- Questions asked
- Most used docs
- Unanswered queries
- Token usage
- Latency
- Active users
Answer Quality Policy
Knowforge must only answer using retrieved trusted sources.
If relevant context is weak or unavailable:
System should respond clearly that it does not have enough information.
No fabricated answers.
Non Functional Requirements
Performance
- Search P95 < 500ms
- Chat P95 < 4s
- Async indexing
Scalability
- 100+ tenants MVP benchmark
- 50k+ documents testable architecture
- Horizontal worker scaling
Reliability
- Retry failed jobs
- Health checks
- Monitoring
- Graceful degradation
Security
- Tenant isolation
- Secure secrets handling
- Role-based permissions
- Audit logs
- Encrypted storage
Observability
- Structured logs
- Metrics
- Traces
- Correlation IDs
Technical Architecture
Frontend
Next.js
Backend
FastAPI
Workers
Celery + Redis
Database
PostgreSQL
Vector Search
pgvector
Storage
S3 compatible object storage
AI Layer
LLM abstraction supporting OpenAI / Bedrock
Infra
Docker
Terraform
CI/CD pipelines
High-Level System Flow
Upload Flow
- User uploads file
- File stored in object storage
- Document record created
- Worker processes file
- Chunks + embeddings created
- KB updated
Chat Flow
- User asks question
- Resolve tenant
- Retrieve relevant chunks
- Build prompt
- Generate answer
- Return response with citations
Multi-Tenant Strategy
Initial model:
Shared database + shared tables + tenant_id isolation
Isolation layers:
- DB filtering
- Vector retrieval filtering
- Cache namespacing
- Storage namespacing
- Role-scoped access
Future upgrades:
- Schema per tenant
- Dedicated enterprise infra
Success Metrics
Product Metrics
- Time to first chatable KB < 5 min
- Documents indexed/day
- Weekly active tenants
- Questions per tenant
Quality Metrics
- Citation rate
- Unanswered query %
- Retrieval relevance score
Engineering Metrics
- API latency
- Worker throughput
- Concurrent users supported
- Cost per 100 chats
Risks
Hallucinations
Mitigation:
- Retrieval grounding
- Citations
- No-answer fallback
Tenant Leakage
Mitigation:
- Tenant scoped queries
- Isolation tests
- Access guards
High LLM Costs
Mitigation:
- Cache repeated prompts
- Efficient chunk retrieval
- Usage limits
Poor Search Quality
Mitigation:
- Better chunking
- Metadata filtering
- Evaluation dataset
MVP Scope
Included:
- Auth
- Multi-tenant workspaces
- File uploads
- Background indexing
- Semantic retrieval
- AI chat with citations
- Dashboard
- Basic analytics
- Cloud deployment
Excluded:
- Billing
- SSO
- OCR advanced flows
- Custom models
- Workflow approvals
Roadmap
Phase 1 — MVP
Core platform usable end-to-end.
Phase 2 — Growth
- Embeddable widget
- Better analytics
- Public API
- Usage plans
Phase 3 — Enterprise
- SSO
- Audit exports
- Dedicated environments
- Advanced controls
Launch Definition of Done
- Production deployed
- CI/CD active
- Monitoring enabled
- Load tested
- Tenant isolation tested
- Documentation complete
- Demo tenant seeded
Positioning Statement
Knowforge is the fastest way for growing teams to turn messy documentation into an AI-powered knowledge base.
Elevator Pitch
Knowforge converts scattered company knowledge into searchable, chat-enabled workspaces using RAG, with multi-tenant SaaS architecture and production-ready scalability.
PRD — Knowforge
Product Name
Knowforge
One-Line Description
Knowforge helps startups and small businesses turn scattered documentation into searchable, AI-chat-enabled knowledge bases in minutes.
Executive Summary
Knowforge is a multi-tenant SaaS platform that allows organizations to upload existing documentation and instantly transform it into an organized knowledge base powered by Retrieval-Augmented Generation (RAG).
Users can upload files such as PDFs, DOCX, Markdown, text files, and internal documentation. Knowforge automatically processes content, structures information, enables semantic search, and provides an AI chat assistant capable of answering questions using trusted company sources.
The platform is designed around speed, simplicity, tenant isolation, and scalable infrastructure.
Problem Statement
Most growing teams already have valuable knowledge, but it is fragmented across:
This causes:
Core Value Proposition
Upload your files today.
Get a searchable and chat-enabled knowledge base in minutes.
Primary Goals
Secondary Goals
Non Goals (MVP)
Target Users
Primary ICP
User Roles
Owner
Workspace owner managing users and settings.
Admin
Manages content, analytics, permissions.
Editor
Uploads and updates documentation.
Viewer
Consumes internal knowledge.
External User
Uses public KB or support chat.
Key Use Cases
Startup Onboarding
Upload SOPs, policies, team docs.
Ask:
Ecommerce Support
Upload shipping, returns, warranty docs.
Ask:
Product Documentation
Upload manuals and guides.
Ask:
Internal Search
Ask:
Product Principles
Functional Requirements
1. Authentication
2. Multi-Tenant Workspaces
3. Document Management
Supported formats:
Features:
4. Automatic Knowledge Structuring
AI-assisted:
Human override allowed.
5. Ingestion Pipeline
When files are uploaded:
6. Semantic Search
7. AI Chat (RAG)
8. Knowledge Base Portal
9. Analytics Dashboard
Track:
Answer Quality Policy
Knowforge must only answer using retrieved trusted sources.
If relevant context is weak or unavailable:
System should respond clearly that it does not have enough information.
No fabricated answers.
Non Functional Requirements
Performance
Scalability
Reliability
Security
Observability
Technical Architecture
Frontend
Next.js
Backend
FastAPI
Workers
Celery + Redis
Database
PostgreSQL
Vector Search
pgvector
Storage
S3 compatible object storage
AI Layer
LLM abstraction supporting OpenAI / Bedrock
Infra
Docker
Terraform
CI/CD pipelines
High-Level System Flow
Upload Flow
Chat Flow
Multi-Tenant Strategy
Initial model:
Shared database + shared tables + tenant_id isolation
Isolation layers:
Future upgrades:
Success Metrics
Product Metrics
Quality Metrics
Engineering Metrics
Risks
Hallucinations
Mitigation:
Tenant Leakage
Mitigation:
High LLM Costs
Mitigation:
Poor Search Quality
Mitigation:
MVP Scope
Included:
Excluded:
Roadmap
Phase 1 — MVP
Core platform usable end-to-end.
Phase 2 — Growth
Phase 3 — Enterprise
Launch Definition of Done
Positioning Statement
Knowforge is the fastest way for growing teams to turn messy documentation into an AI-powered knowledge base.
Elevator Pitch
Knowforge converts scattered company knowledge into searchable, chat-enabled workspaces using RAG, with multi-tenant SaaS architecture and production-ready scalability.