quedote

byVishnu Reddy

Build a production-ready B2B SaaS web app called “Questionnaire Copilot”. PRODUCT: An AI Security Questionnaire Autofiller for small/mid-sized B2B SaaS companies. PROBLEM: Companies receive 50–500+ question security questionnaires in Excel, CSV, PDF or DOCX. Employees manually search security policies, SOC 2 reports and previous questionnaires to answer them. CORE WORKFLOW: Upload questionnaire → Extract questions → Search company knowledge → Generate evidence-backed answers → Show confidence + citations → Human reviews/edits → Export completed questionnaire CRITICAL RULE: NEVER hallucinate. If reliable evidence is unavailable, mark: “Insufficient evidence — human review required.” TARGET USERS: 10–100 employee B2B SaaS/technology companies that regularly receive security questionnaires. V1 MUST HAVE: 1. AUTHENTICATION - Sign up/login - Company/workspace - Secure multi-tenant data isolation 2. DASHBOARD Show: - Recent questionnaires - Total questions - Answered - Needs review - Insufficient evidence - Completion percentage 3. KNOWLEDGE BASE Allow upload of: - PDF - DOCX - TXT - CSV - XLSX Typical documents: SOC 2 reports, security policies, privacy policies, incident-response policies, BCP/DR documents, architecture documentation and previous questionnaires. Processing: Upload → extract text → chunk → index → searchable knowledge. 4. QUESTIONNAIRE UPLOAD Accept: - XLSX/XLS - CSV - PDF - DOCX Automatically detect and extract questions. Display: “127 questions detected.” 5. AI ANSWERING For every question: - Retrieve relevant company documents - Retrieve previous approved answers - Generate answer ONLY from retrieved evidence - Calculate confidence - Attach citations - Flag unsupported questions Structured output: { "answer": "...", "confidence": 0.96, "status": "answered", "citations": [ { "document": "Access Control Policy.pdf", "page": 4, "excerpt": "..." } ] } Statuses: - answered - needs_review - insufficient_evidence - not_applicable If evidence is insufficient: { "answer": null, "confidence": 0, "status": "insufficient_evidence" } 6. QUESTIONNAIRE WORKSPACE Show each question with: Question AI answer Confidence Status Evidence/source Relevant excerpt Actions: - Approve - Edit - Regenerate - Mark N/A Filters: All / Answered / Needs Review / Insufficient Evidence / Approved Categories: Security, Privacy, Access Control, Encryption, Infrastructure, Data Protection, Incident Response, Business Continuity, Compliance, Third Party Risk, AI Security, Other. 7. APPROVED ANSWER MEMORY When a user approves an answer, store it. Use semantic matching so similar future questions can reuse previous approved answers. Example: “Is customer data encrypted at rest?” and “Do you encrypt stored customer information?” should identify the previous approved answer as relevant. 8. EVIDENCE Every generated answer should show: - Source document - Page/section where available - Relevant excerpt - Confidence The user must be able to inspect the evidence before approving. 9. EXPORT Export the completed questionnaire as: - XLSX - CSV - DOCX For Excel, preserve the original questionnaire structure and place answers into the appropriate answer fields. Optional export: - Answers only - Answers + evidence 10. BILLING Stripe subscriptions. FREE: 1 questionnaire/month 25 questions 5 documents STARTER: $29/month 10 questionnaires 1,000 questions 50 documents PRO: $79/month Unlimited questionnaires 5,000 questions/month Unlimited documents 11. LANDING PAGE Headline: “Answer security questionnaires in minutes, not days.” Subheading: “AI answers questionnaires using your company's approved documents and previous answers—with evidence for every response.” CTA: Start Free Explain: Upload → Analyze → Evidence-backed answers → Review → Export. 12. SECURITY Use: - Secure authentication - Multi-tenant isolation - Row-level security - Private file storage - Server-side API keys - Audit logs Log: document_uploaded questionnaire_created answer_generated answer_edited answer_approved questionnaire_exported TECH STACK: Frontend: Next.js + TypeScript + Tailwind + shadcn/ui Backend: Next.js API/server actions Database: Supabase PostgreSQL Storage: Supabase Storage AI: OpenAI API with structured outputs and retrieval/RAG. Payments: Stripe Deployment: Vercel + Supabase 13. DEMO MODE Create fictional company “Acme Cloud” with sample: - Security Policy - Access Control Policy - Incident Response Policy - Privacy Policy - BCP Include 15 sample questionnaire questions so users can immediately test the product. 14. DO NOT BUILD IN V1 Do NOT build: - Slack/Teams integrations - AWS/Okta integrations - Full GRC - SOC 2 management - Vendor management - Risk registers - Mobile app - Browser extension - Complex admin roles - AI agents V1 ONLY needs: QUESTIONNAIRE → KNOWLEDGE → AI ANSWER → EVIDENCE → HUMAN APPROVAL → EXPORT IMPORTANT: Build the actual working application, not a UI prototype. The acceptance test is: Create account → upload company documents → upload Excel questionnaire → extract questions → generate evidence-backed answers → review/edit → approve → export completed questionnaire. Prioritize a simple working MVP over unnecessary features.