Documentation Index
Fetch the complete documentation index at: https://cernio.gadulabs.com/llms.txt
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Cernio — MASTER PRD v3.5
March 2026 — Categories A-G completed (v0.74), transitioned to Ring 1-4 priority structure
Source Documents:
- Founder Bible:
docs/handbook/ (15 atomic files, index: docs/handbook/INDEX.md)
- Strategy:
docs/strategy/INDEX.md (8 architectural decision documents, Ring 1-4)
- Handbook Alignment Report:
docs/HANDBOOK_ALIGNMENT_REPORT.md
- Task List:
docs/TODO.md (Ring 1-4, ~106 atomic tasks)
1. Vision
Finding the best-fit buyer candidates for any product + target market using AI, prioritizing them, and facilitating contact with the right decision maker.
DOSE Chemicals = Founder’s own company (super admin + first tenant). Free indefinitely — first real revenue will come from external customers.
Goal: Invite-only beta (upon Ring 1 completion). Long-term: Multi-tenant SaaS — “B2B Buyer Intelligence Platform” (Founder Bible Ch. 120-121).
Handbook: 01-vision-product.md (vision, market, ICP, WOW moment)
Handbook: 07-competitive-landscape.md (competition, positioning, “B2B Buyer Intelligence Platform” category creation)
2. Current System (Working State)
Data Collection Pipeline
[AI Discovery] → discover/route.ts → companies table
[Bulk Script] → bulk_fixer.js → companies update + contacts
[Headhunt UI] → headhunt/route.ts → contacts table
[Batch Headhunt] → finder.js → contacts table (batch)
[DB Cleanup] → cleaner.js → duplicate removal + segment audit
Pages
/companies — Company list, FitScore badge, company_type filter, headhunt, modal detail/contacts — Contact directory, filter/sort, pagination/discovery — AI company discovery (4 providers, cache, confidence scoring)/leads — Lead pipeline, status/priority, detail page, interaction + task CRUD/scraper — File upload (PDF/Excel/Word) → review → Supabase push/admin/segments — Segment definitions CRUD
3. Module Status
Completed (v0.1-v0.74, Categories A-G)
| Module | Description |
|---|
| AI Pipeline Quality (A) | Confidence scoring (4 pipelines), company_type classification, entity validation, domain dedup, marketplace blacklist |
| Code Architecture (B) | Discovery orchestrator (9 steps), DB layer (7 modules), API standard response |
| Prompt Architecture (C) | Central prompt builder (lib/prompts.ts), segment/company_type dynamic inject |
| FitScore v2 (D) | 6-factor score, batch rescore, breakdown table |
| Database (E) | 18 tables, domain/description/confidence columns, composite uniques |
| UI/UX (F) | Company_type badge, segment filter, provider selector, feedback buttons |
| Lead Management (G) | Lead pipeline (6 statuses), detail page, interaction + task CRUD |
| Security (H1 partial) | SEC-A (12 routes validateApiKey), SEC-B (client-side Supabase → API, 3 endpoints) |
Ring 1: Launch Blocker (next up — 62 tasks)
Strategy documents: docs/strategy/01-08
| # | System | Tasks | Strategy |
|---|
| R1-1 | Auth & Multi-Tenant | 14 | 01-auth-multi-tenant.md |
| R1-2 | API Cost Control | 8 | 02-api-cost-control.md |
| R1-3 | Pre-Action Confirmation | 7 | 05-usage-confirmation.md |
| R1-4 | Billing & Credit | 18 | 04-billing-credits.md |
| R1-5 | Security Hardening | 3 | (existing SEC-B2/D/E2) |
| R1-6 | Monitoring Foundation | 3 | 07-monitoring-admin.md |
| R1-7 | Onboarding & Activation | 9 | 08-onboarding-activation.md |
Ring 2: Retention (44 tasks)
| # | System | Tasks | Strategy |
|---|
| R2-1 | AI Pipeline Quality Improvement | 16 | 03-ai-pipeline-quality.md |
| R2-2 | Batch Operations UI | 11 | 06-batch-operations.md |
| R2-3 | Monitoring & Dashboard | 14 | 07-monitoring-admin.md |
| R2-4 | UI/UX Design System | 3 | — |
Rings 3-4: Differentiation & Scaling (not yet atomized)
Strategy documents will be written after R2 is complete, tasks will be extracted.
- R3: Data Moat, Export Intelligence, Trade Fair, HubSpot, Competitive Intel
- R4: Background Job Queue, Worker, CI/CD, Mobile, AI Copilot
Cancelled / Deferred
| Module | Reason |
|---|
| LinkedIn Automation | High risk of LinkedIn bot ban |
| Email Follow-Up / Sequencing | HubSpot already handles this |
| Sample Automation | No regular monthly sample workflow |
4. FitScore v2 — Current
Handbook: 02-ai-discovery-pipeline.md Ch. 19 (FitScore formula)
Handbook: 13-discovery-code-architecture.md Ch. 243-244 (scoring implementation)
FitScore v2 (Active — lib/scoring/fitScore.ts)
FitScore (0-100) — 6 Factors:
Segment Match (max 25): Alignment with DOSE segment
Company Type (max 25): distributor=25, reseller=15, end_user=10, manufacturer=5
Contact Quality (max 20): 1+ person + email=20, 1+ person=12, none=0
Website (max 10): exists=10, none=0
Description (max 10): 50+ chars=10, short=5, none=0
Confidence (max 10): AI confidence score (0-1) x 10
export_ai_company_scores table.
Batch rescore: POST /api/score — rescores all companies.
Post-discovery: Automatic scoring + breakdown saved.
5. HubSpot Integration (Phase 3)
Handbook: 08-product-roadmap.md Ch. 121 (Stage 4, CRM integration)
HubSpot is used for mail/follow-up/sequences. Integration plan:
- Sync HubSpot activity to the
interactions table
- Push new contacts to HubSpot as well
- Can be triggered via n8n webhook
6. DB Schema
Handbook: 09-database-schema.md — 22 table details (Ch. 136-168)
Current Tables (18/22, RLS active)
export_ai_organizations, export_ai_profiles, export_ai_companies,
export_ai_contacts, export_ai_interactions, export_ai_tasks,
export_ai_products, export_ai_quotes, export_ai_quote_items,
export_ai_search_history, export_ai_segments, export_ai_leads,
export_ai_lead_contacts, export_ai_company_scores, export_ai_search_results,
export_ai_search_queries, export_ai_search_feedback, export_ai_ai_job_runs
Planned Tables (by Ring)
| Table | Ring | Strategy |
|---|
export_ai_organization_members | R1-1 | 01-auth |
export_ai_usage_daily | R1-2 | 02-cost |
export_ai_plan_limits | R1-4 | 04-billing |
export_ai_credit_wallets | R1-4 | 04-billing |
export_ai_credit_transactions | R1-4 | 04-billing |
export_ai_usage_monthly | R1-4 | 04-billing |
export_ai_subscriptions | R1-4 | 04-billing |
export_ai_activity_log | R1-6 | 07-monitoring |
export_ai_market_context | R2-1 | 03-pipeline |
export_ai_api_metrics | R2-3 | 07-monitoring |
7. Pricing & Credit Model
Handbook: 05-pricing-credit-economy.md Ch. 68-84
Plans (April 2026 — BILL-19 + R0-8 decisions)
| Plan | Price | Searches/month | Companies/search | Contact reveals | Saved leads |
|---|
| Free | $0 | 5 | 10 | 0 (gated) | 10 |
| Pro | $49/mo | 50 | 25 | 100 | Unlimited |
| Team | $149/mo | 200 | 25 | 500 | Unlimited |
Credit Costs
- Discovery search: 1 credit
- Contact reveal: 1 credit
- Deep analysis: 2 credits
- Market intel: 3 credits
Unit Economics
- Target: $0.06/search cost
- LTV/CAC target: >3x
8. Long-Term Vision (5-Stage Evolution)
Handbook: 08-product-roadmap.md Ch. 116-135
Stage 1: Discovery → Product + Country → Ranked Companies
Stage 2: Contact Intelligence → Decision maker finding, enrichment
Stage 3: Lead Workspace → CRM-like workflow, status pipeline
--- CURRENT STAGE: Ring 1 (auth, billing, onboarding) → invite-only beta ---
Stage 4: Trade Fair + Mobile → Card scan, meeting notes (Ring 3)
Stage 5: B2B Buyer Intelligence Platform → AI Copilot, market intelligence (Ring 4)
9. Go-to-Market Strategy
Handbook: 06-go-to-market.md Ch. 85-100
- First 10 users: Personal network + trade fair contacts (Ch. 89)
- Activation metric: Running a discovery in the first session (Ch. 98)
- Product-led growth: Freemium → Pro upgrade funnel
- GTM flywheel: Discovery → Value → Share → Referral
10. Principles
Human-in-the-Loop: AI prepares the draft, human approves. External communications are never fully automated.
Priority order: Ring 1-4 concentric rings. Dependency order is followed within the same Ring.
Cost: search_history cache — if the same query was run recently, skip the AI call.
Scope discipline (Ch. 211): “The biggest risk is not technical — it’s scope explosion.”
