From invisible gaps to complete supplier emissions coverage.

AI gap-mapping and predictive modelling fill missing data and give you a full picture of your supply chain.

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Our impact

Why Coverage Matters

Your biggest emissions often hide where the data is missing.

Even with supplier outreach, non-responders, partial submissions, and inconsistent boundaries leave critical blind spots. These gaps distort Scope 3 baselines, increase compliance risk, and make targeted decarbonisation difficult.

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The Complete Coverage Workflow

Three AI-led steps reveal the full supply chain picture.

Supplier Engagement Summary table listing suppliers, part names, validation status with color-coded labels, timestamps, and view links, alongside critical and partial gaps legend.Dashboard interface showing supplier engagement details with progress bars and alerts for data updates and new submissions.Chart showing supplier data breakdown with progress bars for Manufacturing, Logistics, and Raw Materials, divided into Primary Data, Secondary Data, and AI Enriched Data.Dashboard showing Supplier Engagement Summary with supplier validation statuses, engagement details of companies, alerts and notifications, and supplier data breakdown by manufacturing, logistics, and raw materials with primary, secondary, and AI enriched data percentages.
Identify

Gap Detection

Automated mapping highlights what is missing by supplier, category, and region.

Coverage views show completeness across every level.

Alerts highlight where emissions risk may be hidden.

Engage

Automated Supplier Follow-Up

Smart engagement workflows close gaps at scale without extra headcount.

Guided workflows make it simple for suppliers to provide complete data.

Automated reminders and tracking lift response rates and maintain consistency.

Fill

Predictive Emissions Modelling

Predictive modelling completes unavoidable gaps with accurate, AI-generated estimates.

Benchmarking compares suppliers and categories to reveal real emissions drivers.

Modelled outputs give you full visibility even when primary data is missing.

Supplier Engagement Summary table listing suppliers, part names, validation status with color-coded labels, timestamps, and view links, alongside critical and partial gaps legend.
Identify

Gap Detection

Automated mapping highlights what is missing by supplier, category, and region.

Coverage views show completeness across every level.

Alerts highlight where emissions risk may be hidden.

Dashboard interface showing supplier engagement details with progress bars and alerts for data updates and new submissions.
Engage

Automated Supplier Follow-Up

Smart engagement workflows close gaps at scale without extra headcount.

Guided workflows make it simple for suppliers to provide complete data.

Automated reminders and tracking lift response rates and maintain consistency.

Chart showing supplier data breakdown with progress bars for Manufacturing, Logistics, and Raw Materials, divided into Primary Data, Secondary Data, and AI Enriched Data.
Fill

Predictive Emissions Modelling

Predictive modelling completes unavoidable gaps with accurate, AI-generated estimates.

Benchmarking compares suppliers and categories to reveal real emissions drivers.

Modelled outputs give you full visibility even when primary data is missing.

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99%

supplier coverage across the supply chain
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3x

faster gap closure with automated engagement
Vertical infographic with four horizontal steps labeled 01 to 04, showing progress through a process with block icons and placeholder text.

15-20%

higher baseline accuracy from predictive modelling
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100%

transparency between reported and modelled values

The Impact of Insight

From partial visibility to full coverage.

Complete Coverage = Confidence in Reporting and Decarbonisation

No blind spots. No guesswork.

With Insight, you can stand behind your Scope 3 data with confidence. No more uncertainty about missing suppliers or hidden emissions. Mavarick gives you a complete, transparent foundation for reporting and real decarbonisation action.

fewer errors in supplier data submissions.