AI-powered normalization of climate data for flawless ERP carbon accounting.
Enterprise teams struggle to integrate disparate climate data sources into their existing ERP systems, causing inaccurate carbon accounting and regulatory compliance risks.
EcoNormalize uses AI to reconcile and standardize data from multiple climate sources, resolving inconsistencies like unit mismatches or scope definitions. It generates ERP-ready payloads with confidence scores, reducing manual reconciliation by 90%. Built-in validation ensures compliance with GHG Protocol standards.
Sustainability and ESG teams in large enterprises managing carbon accounting and regulatory reporting
AI reconciliation engine trained on carbon datasets—beats manual mapping in accuracy and speed.
supportive
Auto-convert units, scopes, and formats to GHG standards.
Merge/resolve conflicts from 5+ sources with diff viewer.
ML scores data quality; flag low-confidence entries.
Generate CSV/API payloads for direct ERP import.
Pre-built checks for CSRD, SEC climate rules.
Upload CSVs for bulk normalization.
Fine-tune model on user data (Enterprise).
Webhook endpoints for programmatic use.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| tier | text | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| name | text | No |
| sources | text[] | No |
| status | text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| dataset_id | uuid | No |
| original_data | jsonb | No |
| normalized_data | jsonb | No |
| confidence_score | float | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | Yes |
| name | text | No |
| rules | jsonb | No |
Relationships:
/api/datasetsCreate dataset from sources
/api/normalize/:datasetIdRun AI normalization
/api/normalizations/:id/exportDownload ERP payload
/api/rulesetsList validation rules
100MB upload
1GB/month
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 25 | 12% | $45 | $540 |
| Month 6 | 200 | 18% | $432 | $5,184 |
Turn messy sources into ERP-ready carbon metrics—accurate, compliant, effortless.
Post in ESG LinkedIn groups and Twitter threads on 'carbon data challenges'; DM 20 leads offering free normalization of their sample data. Use Typeform survey for pain validation, convert top 3 to Pro.
Enterprise scale
No AI normalization focus
Affordable AI for mid-market
CRM integration
Limited climate sources
Source-agnostic AI
Proprietary AI models improve with anonymized user data; switching cost from custom rules.
AI maturity + rising Scope 3 reporting mandates create demand for smart data tools.
AI accuracy issues
Human review + iterative training
Low AI trust
Confidence scores + audits
Data privacy
GDPR compliant, no data retention
Success: 70% pain match
Success: 80% satisfaction
Success: 20% referral rate
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