Question 1

What sustainability intelligence is built into the AI?

Accepted Answer

Our AI functionality, which includes 19 collaborative agents, was developed and is continuously reviewed by team of 21 on-staff climate scientists and AI engineers. Our team has documented our AI insights in 15 papers and AI conferences. In addition our product footprinting features were developed in consult with sustainability leaders at more than 20 major companies with complex supply chains. Finally, Watershed AI has an extensive materials library and a database of 500,000 emissions factors built into the platform.

Question 2

Does the AI system provide an indication of confidence levels or uncertainty ranges for key AI-assisted datapoints?

Accepted Answer

Yes. Watershed includes both materials match scores and emissions mapping scores to help the user understand the confidence level of each mapping.

Question 3

How does Watershed handle vague or messy purchasing data?

Accepted Answer

Our AI-powered system enriches and classifies even incomplete or vague data—like “metal fastener” or “resin compound”—into structured inputs for PCF creation. We handle deconstruction, uncertainty scoring, and HS code classification so you can get moving without needing perfect inputs on day one.

Question 4

Can I connect Watershed Product Footprints to my corporate GHG inventory?

Accepted Answer

Absolutely. Watershed's PCFs sync directly into your corporate footprint, so you can see how material-level changes ripple through to Scope 3.1 emissions. That means you’re not just measuring—you’re managing, optimizing, and proving reductions across your value chain.

Question 5

Can Watershed product footprints incorporate supplier-specific data?

Accepted Answer

Yes. You can inject primary data at any level—from facility energy use to sourcing region to process changes—so your PCFs reflect business reality, not generic assumptions. This means you can track reductions you’ve already made, simulate future actions, and prioritize what data to collect from suppliers next.

Question 6

Can Watershed simulate the impact of procurement changes or product redesigns?

Accepted Answer

Yes. Watershed lets you model “what-if” scenarios—like switching suppliers, adding recycled content, or using clean energy—so you can compare options before making decisions. These simulations help prioritize high-impact actions and show the carbon ROI of procurement strategies.

Question 7

Can I see a live test using data relevant to my supply chain?

Accepted Answer

Yes, Watershed can provide a live test of AI mapping or recommendations using data relevant to your business.

Question 8

How accurate are Watershed’s upstream PCFs compared to spend-based estimates or EFs from databases?

Accepted Answer

Spend-based estimates give you a rough direction; Watershed’s production graphs give you a clear map. Our system deconstructs each material into its upstream components and processes, using global supply chain intelligence and probabilistic modeling to yield much more granular and accurate results than static emissions factors.

Question 9

Can Watershed demonstrate validation datasets and benchmarking results for its AI??

Accepted Answer

Yes, we will be able to demonstrate validation datasets and benchmarking results for AI use in our platform.

	Watershed Product Footprints	Other solutions
Automated mapping to single activity-based EF	✔	✔
Advanced AI to go beyond single EF mappings	✔	❌
Instant AI digital twin of your unique supply chain	✔	❌
Product footprints you can edit, refine, and test	✔	❌
Supports any industry	✔	❌
Hallucination safeguards	✔	❌
Infused with deep sustainability intelligence	✔	❌
Built by team of leading climate science researchers and AI experts	✔	❌
Trusted by world’s largest supply chains	✔	❌

Sustainable procurement, powered by AI

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Join the Sustainability AI Summit

Learn how companies are using Product Footprints

How Watershed approaches AI

How it works

Automate activity-based Scope 3.1 measurement

View product footprints for every material in your supply chain

Find decarb hotspots in your supply chain

Compare suppliers, materials, and variants

Simulate the impact of potential decarbonization levers

Sync product footprints with your corporate footprint

See it in action with some of your own materials

Watershed vs. other solutions

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Book a demo

FAQ

Product tours

Published papers on Sustainability AI

Criteria for credible AI-assisted carbon footprinting systems: The cases of mapping and lifecycle modeling

A spend classification benchmark for estimating scope 3 carbon emissions

An LLM-based approach to creating a carbon emissions reduction levers library at scale