Sustain reads the supplier and emissions data you already collect, prices the exposures hiding in it, and returns a ranked list of moves. Each one carries a euro figure, an owner and a deadline.
No language model produces these numbers. Turn the model off entirely and every figure is byte-for-byte identical. We prove it with a test that runs on every release.
01 / Upload
Drop in the ESG and operational data you already produce. Spreadsheets, reports, site data, energy and emissions records, audits.
02 / Understand
Each value keeps its unit, its reporting year, and the document and row it came from. The validator quarantines what it cannot accept rather than guessing.
03 / Reason
Sustain walks a private knowledge graph with authored rules. One qualified supplier, a long lead time and a single region of origin add up to a dependency.
04 / Price
Sustain prices each exposure on its own, with a seeded Monte Carlo run. You get an expected impact and a p95 downside.
Illustrative figures from a representative dataset. Not a customer result.
05 / Act
You get one ranked decision, and you can open any figure in it back down to the document it came from.
Illustrative figures from a representative dataset. Not a customer result.
01 / Upload
Drop in the ESG and operational data you already produce. Spreadsheets, reports, site data, energy and emissions records, audits.
02 / Understand
Each value keeps its unit, its reporting year, and the document and row it came from. The validator quarantines what it cannot accept rather than guessing.
03 / Reason
Sustain walks a private knowledge graph with authored rules. One qualified supplier, a long lead time and a single region of origin add up to a dependency.
04 / Price
Sustain prices each exposure on its own, with a seeded Monte Carlo run. You get an expected impact and a p95 downside.
05 / Act
You get one ranked decision, and you can open any figure in it back down to the document it came from.
Board decisions get made on these numbers. Choose any layer to go back to the moment in the sequence that produced it.
No language model produces any of these numbers. Turn the model off entirely and every figure is byte-for-byte identical. We prove it with a test that runs on every release.
We do not use anything you upload to train or fine-tune a model, ours or a third party's. The reasoning, simulation and ranking run on Sustain's own deterministic code. One external model takes part: Mistral, our AI sub-processor, composing an answer in Ask or helping read a difficult document, for that single request and nothing else.
See your own data become a ranked set of decisions.
One price per company size. Everything included.