ZeroForge

AI reconciles and fills gaps in multi-source emissions data for audit-proof net-zero reports.

Score: 6.1/10SSHard Build
Brand Colors

The Opportunity

Problem

Enterprise sustainability teams struggle to consolidate emissions data from multiple sources due to data silos in climatetech products, hindering accurate net-zero reporting.

Solution

ZeroForge ingests data from any source, uses AI to detect inconsistencies, reconcile duplicates, and impute missing values based on industry benchmarks. Teams get a single reconciled dataset with confidence scores and one-click reports. Achieve reporting accuracy without manual fixes.

Target Audience

Enterprise sustainability teams managing climatetech tools for emissions tracking and reporting

Differentiator

AI-powered reconciliation engine trained on public emissions datasets, handling 90% of data issues automatically.

Brand Voice

supportive

Features

Multi-Source Upload

must-have12h

Upload CSV/API data from any climatetech tool.

AI Reconciliation

must-have25h

Auto-detect/merge duplicates, standardize units, flag anomalies.

Gap Imputation

must-have20h

AI fills missing data using peer benchmarks and trends.

Confidence Dashboard

must-have10h

Visualize reconciled data with AI confidence scores per metric.

Report Generator

must-have12h

Auto-generate reconciled reports with audit trails.

Benchmark Library

nice-to-have8h

Compare against industry averages.

Export with Logs

nice-to-have6h

Downloads include reconciliation explanations.

Batch Processing

nice-to-have5h

Upload and process multiple files at once.

Total Build Time: 98 hours

Database Schema

users

ColumnTypeNullable
iduuidNo
emailtextNo

uploads

ColumnTypeNullable
iduuidNo
user_iduuidNo
file_urltextNo
statustextNo

Relationships:

  • foreign key to users.id

reconciled_data

ColumnTypeNullable
iduuidNo
upload_iduuidNo
scopetextNo
co2efloatNo
confidencefloatNo
ai_notestextYes

Relationships:

  • foreign key to uploads.id

reports

ColumnTypeNullable
iduuidNo
upload_iduuidNo
generated_attimestampNo

Relationships:

  • foreign key to uploads.id

API Endpoints

POST
/api/uploads

Upload data file

🔒 Auth Required
POST
/api/reconcile/:uploadId

Trigger AI reconciliation

🔒 Auth Required
GET
/api/reconciled-data

Fetch reconciled dataset

🔒 Auth Required
GET
/api/reports/:id

Download report

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Tailwind + shadcn/ui
Backend
Next.js + OpenAI API
Database
Supabase
Auth
Supabase Auth
Payments
Stripe
Hosting
Vercel
Additional Tools
Supabase StorageVercel AI SDK

Build Timeline

Week 1: Upload and auth

18h
  • File upload
  • Basic processing
  • DB

Week 2: AI core

30h
  • Reconciliation prompts
  • Confidence scoring

Week 3: Dashboard

22h
  • Viz with scores
  • Imputation

Week 4: Reports and payments

15h
  • Report gen
  • Stripe

Week 5: Polish

12h
  • Benchmarks
  • Deploy
Total Timeline: 5 weeks • 97 hours

Pricing Tiers

Free

$0/mo

1k rows

  • 1 upload/month
  • Basic recon

Pro

$25/mo

50k rows/month

  • 10 uploads
  • Full AI
  • Exports

Enterprise

$99/mo

Unlimited

  • Unlimited
  • Custom models
  • API

Revenue Projections

MonthUsersConversionMRRARR
Month 11206%$180$2,160
Month 660012%$1,800$21,600

Unit Economics

$45
CAC
$700
LTV
4%
Churn
85%
Margin
LTV:CAC Ratio: 15.6xExcellent!

Landing Page Copy

AI Fixes Your Messy Emissions Data Automatically

Reconcile silos, fill gaps, report accurately—trusted by sustainability pros.

Feature Highlights

AI duplicate merging
Smart gap filling
Confidence scores
Audit-ready reports

Social Proof (Placeholders)

"'95% accuracy boost' — Head of ESG"
"'No more Excel hell' — Sustain Manager"

First Three Customers

Share AI demo video on LinkedIn ESG groups, offer free reconciliations for feedback. Target attendees of net-zero conferences via email. Use Reddit r/climate to find beta testers willing to share datasets.

Launch Channels

Product Huntr/climateLinkedIn #NetZeroTwitter AI+Sustainability

SEO Keywords

AI emissions reconciliationfix emissions data gapsautomated net zero auditreconcile climatetech data

Competitive Analysis

Climatiq

climatiq.io
Usage-based
Strength

Emission factors

Weakness

No reconciliation

Our Advantage

Data cleaning focus

Salesforce Net Zero

salesforce.com
Enterprise
Strength

CRM integration

Weakness

Vendor lock-in

Our Advantage

AI-agnostic multi-tool

🏰 Moat Strategy

AI improves with proprietary reconciled datasets over time.

⏰ Why Now?

AI advancements + mandatory disclosures create demand for automated accuracy.

Risks & Mitigation

technicalhigh severity

AI hallucinations

Mitigation

Confidence thresholds + human review

financialmedium severity

OpenAI costs

Mitigation

Tiered limits + caching

Validation Roadmap

pre-build7 days

Test AI on sample datasets

Success: 85% accuracy

mvp14 days

5 user betas

Success: Positive NPS >7

Pivot Options

  • Pure data validation tool
  • Benchmarking only
  • API for other SaaS

Quick Stats

Build Time
97h
Target MRR (6 mo)
$1,800
Market Size
$3000.0M
Features
8
Database Tables
4
API Endpoints
4