Scope 3 has always been the hardest part of corporate carbon accounting. The data lives across thousands of suppliers, in dozens of formats, updated on no consistent schedule. Getting from raw spend data to a defensible emissions number, let alone a decarbonization plan, has historically taken teams of analysts months of manual work.
The industry’s response has been more headcount and more labor for already over-burdened teams, but that approach doesn’t scale with the volume of supplier data that meaningful Scope 3 decarbonization requires. As regulatory requirements tighten and investors start asking for reduction plans, that ceiling is becoming increasingly apparent.
At Green Project, we've simplified Scope 3 decarbonization by building AI into the core of your workflows. Not as an add-on, but as the engine behind how our platform works.
With AI doing the heavy lifting, you can:
Every company's spend data looks different: naming conventions, categorizations, levels of granularity. Our AI-powered matching tool takes a customer's raw spend data and normalizes it, then matches suppliers against our proprietary database. What used to require manual cleanup and guesswork now happens automatically, giving buyers a clean, structured starting point for their Scope 3 inventory.
Once your spend data is matched, the next question is what those suppliers have already disclosed, and which ones matter most. Our AI engine sorts suppliers by emissions materiality, then screens each one against CDP, SBTi, and other publicly available sources, pulling out relevant data points automatically instead of leaving someone to read through unstructured PDFs and filings by hand.
That combination does more than save review time: it surfaces where a company's real emission hotspots sit, so the engagement that follows can be targeted at the suppliers who move the needle, rather than treating every supplier the same way.
When our AI agent can’t find publicly available emissions data for a supplier, it’s often a sign that the supplier is low-maturity and hasn’t calculated their footprint before. Sending that supplier a survey they have no way to answer confidently doesn’t move anything forward.
Instead, we take a targeted approach: we give the supplier an AI-powered calculation engine that lets them easily calculate their Corporate Carbon Footprint (CCF), Service Carbon Footprint (SCF), and Product Carbon Footprint (PCF) for the first time.
That data can then be shared back with the buyer, improving the accuracy and completeness of their own Scope 3 reporting.
None of this matters, though, if buyers can't trust the numbers behind it. Our AI-powered data quality checks flag inconsistencies and outliers in supplier-submitted data before it ever reaches a buyer's Scope 3 inventory or informs a procurement decision, so the numbers driving those decisions hold up to scrutiny.
When a supplier’s CCF or PCF gets flagged, in-product messaging walks them through resolving the specific data quality issues our checks identified, so the fix happens directly where the data lives, eliminating the need for lengthy and involved email threads.
Once a supplier’s data passes those checks, buyers can choose to upgrade their Scope 3 figures to incorporate supplier-specific emission factors instead of industry averages. That upgrade can only happen once the underlying data has been verified, ensuring audit-readiness down the line.
Ultimately, that number is only useful if it leads to action. Our AI-powered decarbonization agent takes a company's emissions profile and recommends initiatives tailored to their specific footprint from Giki’s library of 750+ decarbonization actions, helping buyers and suppliers move from measurement to a concrete reduction plan instead of a generic checklist.
These AI capabilities exist to close the gap between measuring a footprint and actually reducing it. The less time that your team spends matching spend data, chasing down supplier disclosures, or reformatting the same numbers for another survey, the more time they have to spend on initiatives that move emissions in the right direction.
We're continuing to expand AI across the Green Project platform, connecting our products more tightly together and extending automation into new areas of reporting and decision-making, all in service of a simple goal: less time producing inventories, and more time reducing emissions.
