Turn incomplete, inconsistent supplier data into trusted, audit-grade data foundation
AI-led workflows ensure complete submissions, and the autonomous engine flags issues, fixes inconsistencies, and fills gaps for full coverage.
AI-led workflows ensure complete submissions, and the autonomous engine flags issues, fixes inconsistencies, and fills gaps for full coverage.

Effective decarbonisation depends on trusted, high-quality data, yet supplier submissions rarely meet that standard. Variability in formats, missing fields, and manual errors create gaps that traditional validation processes cannot fix at scale. These gaps weaken targeting, slow action, and limit the impact of decarbonisation efforts.

Three intelligence-led steps that create complete, consistent, and audit-ready carbon data.

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Supplier Data Platform
AI-led supplier engagement gathers complete submissions at scale.
Automated reminders and progress tracking improve response rates.
Standardised inputs ensure consistency from the start.
AI-Powered Data Validation
The engine detects anomalies, errors, and inconsistencies in real time.
Automated corrections and quality scoring reduce manual review.
A real-time view shows the status and integrity of every submission.
Data Completeness Tracking
Intelligent gap detection highlights missing suppliers, materials, and lanes.
Automated engagement helps close gaps and secure the remaining data.
A coverage view shows completeness across the entire supply chain.




From inconsistent inputs to reliable, audit-ready outputs.
Trusted data is the foundation of effective decarbonisation. Mavarick ensures data integrity at scale, powering complete Scope 3 coverage, sourcing intelligence, and audit-ready compliance so teams can act with confidence.