SheetThink — AI That Fixes Your Spreadsheet Logic, Not Just Your Formulas
AI is great at writing VLOOKUP. It is terrible at telling you that your margin calculation is structurally wrong and your pivot table is measuring the wrong thing. SheetThink audits the reasoning behind your spreadsheet, not just the syntax, and hands you a plain-English diagnosis before your next board meeting.
Difficulty
beginner
Category
NLP & Text AI
Market Demand
High
Revenue Score
7/10
Platform
Web App
Vibe Code Friendly
⚡ YesHackathon Score
🏆 8/10
Validated by Real Pain
— seeded from real-world friction
Users report that AI tools are useful for generating spreadsheet syntax but completely fail at identifying structural reasoning errors in financial models and dashboards — the actual source of bad business decisions.
What is it?
The Reddit signal is sharp: AI fills in SUMIF formulas fine but cannot tell you that your entire cohort analysis is comparing monthly active users against the wrong date column. SheetThink is a Google Sheets add-on where you paste your sheet URL, describe what business question the sheet is supposed to answer, and Claude audits the logical structure — wrong aggregation levels, circular dependencies, misleading chart axes, and broken assumption chains — and returns a prioritized plain-English fix list. It is not a formula autocomplete, it is a spreadsheet logic auditor. The target is the 500k+ Google Sheets power users who build financial models, cohort dashboards, and ops trackers without a data analyst on staff. Buildable in 2 weeks with Google Sheets API, Claude API for reasoning, and a Next.js web interface — no custom model training, no scraping, no compliance issues.
Why now?
Claude claude-3-5-sonnet's structured JSON output mode makes reliable issue extraction from unstructured sheet context a solved problem as of early 2026. Google Sheets API v4 read access is free and requires only a standard OAuth review — this is a 2-week build with no infrastructure risk.
- ▸Paste any Google Sheet URL and describe the business question in plain English — no template, no configuration.
- ▸Claude audits sheet structure for logical errors: wrong aggregation levels, mismatched time periods, circular dependencies, and broken assumption chains.
- ▸Prioritized fix list returned as plain English with the exact cell range and tab name for each issue.
- ▸One-click shareable audit report PDF for sending to clients or investors.
Target Audience
Solo founders, ops managers, and consultants who build complex Google Sheets models without a data analyst — estimated 500k active users based on Google Workspace adoption and r/sheets monthly post volume on logic errors.
Example Use Case
Priya is building a fundraising model for her seed round, pastes her 8-tab Google Sheet, describes the question as 'what is our 18-month runway at three growth scenarios', and SheetThink flags that her burn rate tab is using calendar months while her revenue tab uses 28-day periods — a structural error that would have embarrassed her in the investor meeting.
User Stories
- ▸As a solo founder building a fundraising model, I want AI to audit my sheet logic against my business question, so that I catch structural errors before my investor meeting.
- ▸As a consultant delivering a financial model to a client, I want a shareable audit report PDF, so that I can demonstrate the model has been independently reviewed.
- ▸As an ops manager maintaining a KPI dashboard, I want a monthly logic audit that flags mismatched time periods and wrong aggregation levels, so that I stop presenting bad numbers in team meetings.
Done When
- ✓Sheet reading: done when pasting a Google Sheet URL and granting OAuth returns all tab names and row data in the audit preview within 10 seconds.
- ✓Audit generation: done when submitting a business question returns a structured issue list with at least one identified problem within 60 seconds.
- ✓Report rendering: done when the /report/[id] page displays all issues with severity badges, tab names, cell ranges, and fix suggestions without any blank cards.
- ✓Shareable link: done when clicking Copy Shareable Link produces a URL that opens the full audit report in a new incognito window without any login prompt.
Is it worth building?
$19/month x 80 users = $1,520 MRR at month 2. $49/month x 100 users = $4,900 MRR at month 5. Math assumes 6% conversion from 3,000 signups via ProductHunt and r/sheets.
Unit Economics
CAC: $12 via Reddit free audit offer. LTV: $228 (12 months at $19/month). Payback: 1 month. Gross margin: 90%.
Business Model
$19/month for 10 audits, $49/month unlimited
Monetization Path
Free tier: 2 audits lifetime. Paid tier unlocks monthly audits and shareable audit report links.
Revenue Timeline
First dollar: week 2 via free audit conversion. $1k MRR: month 2. $5k MRR: month 6. $8k MRR: month 12.
Estimated Monthly Cost
Claude API (claude-3-5-sonnet, ~500 audits/month): $35, Vercel: $20, Supabase: $25, Resend: $10, Stripe fees: ~$20. Total: ~$110/month at launch.
Profit Potential
Lifestyle business viable at $3k–$8k MRR.
Scalability
Medium — can expand to Excel file upload, Airtable base auditing, and a shareable audit report link for sharing with investors or clients.
Success Metrics
Week 2: 5 beta audits completed with real user sheets. Month 1: 30 paid subscribers. Month 3: 25+ NPS score from exit surveys.
Launch & Validation Plan
Post in r/financialmodelling and r/sheets offering free audits for complex spreadsheets, collect 20 real audit sessions, measure if users call out at least one issue as genuinely surprising.
Customer Acquisition Strategy
First customer: post in r/financialmodelling offering free audit to anyone sharing a complex model in the thread, run 10 free audits, DM every person who commented to upgrade. Ongoing: LinkedIn content targeting CFOs and ops managers, r/sheets, r/excel, ProductHunt launch, partnerships with financial model template sellers.
What's the competition?
Competition Level
Low
Similar Products
SheetAI adds AI formula writing to Google Sheets but does not audit logic. Coefficient connects Sheets to databases but does not reason about model structure. ChatGPT can audit if you paste manually but has no Sheets integration and no structured report — SheetThink automates the read and returns a professional shareable report.
Competitive Advantage
Logic-level auditing versus syntax-level autocomplete, Google Sheets native versus copy-paste into ChatGPT, shareable report for professional credibility.
Regulatory Risks
Google OAuth requires privacy policy and terms of service before the Sheets API scope is approved. Read-only scope only — never request write access. GDPR: do not store sheet cell data beyond the audit session, store only the issue report.
What's the roadmap?
Feature Roadmap
V1 (launch): Google Sheets audit, issue report, shareable link, Stripe billing. V2 (month 2-3): PDF export, audit history, severity filtering. V3 (month 4+): Excel upload support, scheduled monthly re-audit, team sharing.
Milestone Plan
Phase 1 (Week 1): Google Sheets API reading and Claude audit pipeline working end-to-end in test. Phase 2 (Week 2): Full UI live, Stripe billing gated, 10 beta audits completed with real user sheets. Phase 3 (Month 2): 30 paying subscribers, shareable PDF export live, churn under 10%.
How do you build it?
Tech Stack
Next.js, Google Sheets API v4, Claude API (claude-3-5-sonnet), Supabase, Stripe, Resend — build with Cursor for API layer, v0 for audit report UI, Lovable for onboarding
Suggested Frameworks
Claude claude-3-5-sonnet via Anthropic SDK, Google APIs Node.js client, LangChain for structured output parsing
Time to Ship
2 weeks
Required Skills
Claude API with structured output, Google Sheets API v4 read access, Next.js API routes.
Resources
Anthropic SDK docs, Google Sheets API v4 quickstart, Claude structured output guide, Supabase quickstart.
MVP Scope
app/page.tsx (landing with audit input form), app/api/fetch-sheet/route.ts (Google Sheets API reader), app/api/audit/route.ts (Claude API logic auditor), app/report/[id]/page.tsx (audit report viewer), lib/claude-prompt.ts (structured audit prompt template), lib/db/schema.ts (audits, users, reports), components/IssueCard.tsx (individual issue display), .env.example (GOOGLE_CLIENT_ID, ANTHROPIC_API_KEY, STRIPE_KEY).
Core User Journey
Paste Sheet URL -> describe business question -> receive plain-English audit report in under 60 seconds -> share report link with investor or client -> upgrade to paid for next audit.
Architecture Pattern
User pastes Sheet URL + question -> Next.js API fetches sheet metadata and cell values via Google Sheets API -> Claude API receives structured context and returns JSON issue list -> issues stored in Supabase -> report rendered on /report/[id] -> shareable PDF generated on demand.
Data Model
User has many Audits. Audit has sheet URL, business question, raw cell snapshot (TTL 24h), and one AuditReport. AuditReport has array of Issues each with tab name, cell range, issue type, severity, and plain-English fix.
Integration Points
Google Sheets API v4 for sheet data reading, Claude API (claude-3-5-sonnet) for logic auditing, Stripe for billing, Supabase for audit and user storage, Resend for report email delivery, Vercel for hosting.
V1 Scope Boundaries
V1 excludes: Excel file upload, Airtable auditing, AI auto-fix of formulas, team accounts, API access, audit history beyond 30 days.
Success Definition
A founder pastes their fundraising model, receives an audit report flagging a real structural issue they did not know about, fixes it, and upgrades to paid before sharing the model with investors.
Challenges
The hardest non-technical problem is convincing users their spreadsheet logic is wrong when they built it themselves — no one likes hearing their model is broken. Framing as a confidence check before a board meeting, not a criticism, is the messaging lever. Distribution reality: most spreadsheet power users are not on ProductHunt — r/financialmodelling, r/excel, and LinkedIn are the real acquisition channels.
Avoid These Pitfalls
Do not store raw cell data permanently — financial models contain sensitive data and GDPR deletion requests will be a nightmare. Do not try to auto-fix the spreadsheet in v1 — diagnosis is the value, auto-fix creates liability. Finding first 10 paying customers will take longer than building — run 20 free audits publicly before asking anyone to pay.
Security Requirements
Google OAuth read-only Sheets scope only, Supabase Auth, RLS on audits and issues tables, raw cell data TTL-deleted after 24 hours via Supabase cron, rate limit audit endpoint to 10 req/hour per user, GDPR data deletion endpoint required before Google OAuth review approval.
Infrastructure Plan
Vercel for Next.js, Supabase for Postgres and auth, no file storage needed, GitHub Actions for deploy on main, Sentry for error tracking — total infra under $60/month at launch.
Performance Targets
Expected 80 DAU and 150 audits/day at launch. Audit API response including Claude call under 15 seconds. Report page load under 2s. No caching needed at launch scale — each audit is unique.
Go-Live Checklist
- ☐Security audit complete.
- ☐Payment flow tested end-to-end.
- ☐Sentry error tracking live.
- ☐Vercel Analytics configured.
- ☐Custom domain with SSL live.
- ☐Privacy policy and terms published for Google OAuth review.
- ☐5 beta users completed real audits.
- ☐Rollback: Vercel instant rollback enabled.
- ☐Launch post drafted for r/financialmodelling and ProductHunt.
First Run Experience
On first run: a pre-loaded demo audit of a sample SaaS revenue model sheet is displayed with 4 flagged issues including a time period mismatch and a wrong aggregation level. User can immediately browse the demo report and click each issue to see the cell range and fix suggestion. No manual config required: the demo audit runs against a public read-only Google Sheet with no OAuth needed.
How to build it, step by step
1. Define schema in lib/db/schema.ts: users, audits (sheet_url, question, status), issues (audit_id, tab, cell_range, severity, description, fix_suggestion), reports (audit_id, shareable_slug). 2. Set up Google OAuth 2.0 with read-only Sheets scope in Google Cloud Console and store credentials in .env. 3. Build app/api/fetch-sheet/route.ts to call Google Sheets API v4 spreadsheets.get and spreadsheets.values.batchGet on all tabs, returning tab names, headers, and first 200 rows per tab. 4. Build lib/claude-prompt.ts with a structured system prompt that instructs Claude to return a JSON array of issues with severity, tab, cell_range, and fix fields. 5. Build app/api/audit/route.ts to combine the sheet snapshot and user question, call Claude API with structured output, parse the JSON response, and write issues to Supabase. 6. Build app/report/[id]/page.tsx to render the audit report with severity-colored IssueCards sorted by severity. 7. Add a Copy Shareable Link button that generates a public /report/[slug] URL with no auth required. 8. Add Stripe billing with two price IDs and a gate on the audit endpoint checking the user's monthly audit count. 9. Add Supabase Auth with Google OAuth (reuse the same OAuth app for Sheets access). 10. Deploy to Vercel, run a real Google Sheet through the full audit pipeline end-to-end, and verify a real logical issue is returned in the report.
Generated
April 29, 2026
Model
claude-sonnet-4-6
Disclaimer: Ideas on this site are AI-generated and may contain inaccuracies. Revenue estimates, market demand figures, and financial projections are illustrative assumptions only — not financial advice. Do your own research before making any business or investment decisions. Technology availability, pricing, and market conditions change rapidly; always verify details independently.