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.

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Why Trusted Data Matters

Across large supply chains, supplier submissions vary significantly in quality and completeness, which threatens data integrity.

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.

Two people exchanging a paper showing a bar chart comparing the number of hotel bookings by males and females across different origins.

The Trusted Data Workflow

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

Dashboard showing strategic supplier assessment status with colored square indicators for strategic, secondary, and other suppliers validated; confirmation of 14 requests sent; validation percentages for each supplier category; and risk quality indicators labeled low, medium, and danger.Bar chart showing AI-powered data validation results: 80% validated, 15% pending review, and 5% rejected.Data Quality Score dashboard showing a score of 2.3 with a radar chart rating technological, temporal, and geographical data quality and categories for excellent, fair, and poor ratings.Dashboard showing strategic supplier assessment status, AI-powered data validation with 80% validated, 15% pending review, and 5% rejected, 14 requests sent, and a data quality rating score of 2.3 with a radar chart for technological, temporal, and geographical metrics.
Collect

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.

Validate

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.

Complete

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.

Collect

Supplier Data Collection Platform

AI-led supplier engagement gathers complete submissions at scale.

Guided workflows simplify the process for every supplier.

Automated reminders and progress tracking improve response rates.

Standardised inputs ensure consistency from the start.

Validate

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.

Complete

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.

Dashboard showing strategic supplier assessment status with colored square indicators for strategic, secondary, and other suppliers validated; confirmation of 14 requests sent; validation percentages for each supplier category; and risk quality indicators labeled low, medium, and danger.
Collect

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.

Bar chart showing AI-powered data validation results: 80% validated, 15% pending review, and 5% rejected.
Validate

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 Quality Score dashboard showing a score of 2.3 with a radar chart rating technological, temporal, and geographical data quality and categories for excellent, fair, and poor ratings.
Complete

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.

Minimalist gray outline of a cube with a detached side panel on a white background.

70%

less time spent on manual validation.
Minimalist black background with a faint outline of a hexagonal geometric shape resembling an isometric cube.

80%

fewer supplier data errors.
Vertical infographic with four horizontal steps labeled 01 to 04, showing progress through a process with block icons and placeholder text.

90%+

coverage across suppliers and materials.
Minimalistic gray geometric hexagon shape on a light gray background.

3x

faster audit-ready reporting.

The Impact of Integrity

From inconsistent inputs to reliable, audit-ready outputs.

Every capability starts with trusted data.

Trusted Data = Foundation of the Mavarick Platform

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.