Problem Definition
Problems knowledge workers and researchers face:
- Information Overload: 5.14M+ papers published annually, manual review impossible
- Search Time Waste: Employees spend 1.8 hours/day (9.3 hours/week) searching for information
- Knowledge Disconnect: Research results don’t accumulate, starting from scratch each time
- Context Switching: Moving between sources reduces focus
Market Analysis
| Metric | Value |
|---|---|
| Information Search Time | 20% of work hours |
| Annual Published Papers | 5.14M+ |
| AI Research Tool Adoption | Rapidly growing |
Target Customers: Researchers, analysts, knowledge workers, consultants
Solution: Kerns.ai
Kerns makes research “compound” instead of “reset.”
Core Features
- One-Click Research Reports: Enter topic → comprehensive report generated
- Report Comparison: Compare multiple reports in the same space
- Background AI Tracking: Auto-detects and notifies new developments
- Source Customization: Focus on specific sources or turn off AI knowledge
- Workspace: Personal knowledge base where research accumulates
Differentiation
- Existing tools: Search → Results → Forget
- Kerns: Search → Results → Accumulate → Connect → Grow
Competitive Landscape
| Competitor | Focus | Weakness |
|---|---|---|
| Perplexity | AI search | No accumulation |
| Elicit | Paper analysis | No general research support |
| Consensus | Scientific consensus | Limited versatility |
| Notion AI | Notes + AI | Not research-specialized |
Competition Intensity: High (Red Ocean - many AI search tools)
MVP Development Plan
| Phase | Duration | Scope |
|---|---|---|
| Phase 1 | 2 weeks | Web scraping, source integration |
| Phase 2 | 3 weeks | RAG pipeline construction |
| Phase 3 | 2 weeks | Report generation logic |
| Phase 4 | 3 weeks | Workspace UI |
Total MVP Duration: 8-10 weeks Tech Stack: Python, LangChain, Vector DB, React
Revenue Model
| Plan | Price | Features |
|---|---|---|
| Free | $0 | 3 reports/month, basic sources |
| Pro | $19/mo | Unlimited, all sources |
| Team | $15/user/mo | Shared workspace |
| Enterprise | Contact | API, custom sources |
Expected MRR (12 months): $3,000 - $10,000
Risk Analysis
| Risk | Level | Mitigation |
|---|---|---|
| Technical | Medium | RAG quality is critical |
| Market | High | Competitive, differentiation needed |
| Execution | Medium | Differentiate with “accumulation” feature |
Recommendation
- Domain Fit: productivity, data_mgmt (preferred domains)
- Problem Resonance: Research time waste is a real pain point
- Differentiation Potential: “Compound research” concept is unique
- Scalability: Can expand to B2B market
Overall Score: 81/100