ESG data from 400+ stores and 2,000+ suppliers.
99%+ extraction accuracy.

Every ESG number had to survive public scrutiny.

The source data was never going to arrive in one shape. Utility bills, supplier emails, purchase orders, material-origin certificates, invoices, photos from stores and factories — all of it had to be read, understood, and turned into numbers the business could stand behind. Finding the relevant data buried inside that mix, and turning it into a usable insight, was hard enough on its own.

ESG reports are public documents, and this one would face regulatory and press scrutiny the moment it was filed. That meant extraction accuracy had to be exceptionally high, and every KPI had to be traceable back to the document it came from. The client also had a legal reporting deadline to hit, and wanted to avoid the standing cost of outsourcing the work to a consultancy.

Three constraints were non-negotiable:

• 400+ stores, 2,000+ suppliers, one deadline
• Data ranging from utility bills to material certificates
• Every public KPI needed a paper trail

Pipelines that choose themselves, then check their own work.

The team built a set of AI-powered data pipelines, each tuned to a different kind of source document, with a model automatically routing each incoming file to the right one. The pipelines are multi-modal and multi-model, combining text and vision so a supplier email, a utility bill, and a photograph of a material certificate can each be read the way they need to be read.

Every extraction runs through a verification layer with a self-critique mechanism: when the model’s confidence in a data point drops below threshold, it raises an alert rather than passing the number through silently. Those alerts route into a human review and approval workflow, and full data lineage is kept end to end, so any KPI in the final report can be traced back to the raw document it came from.

All of it — the ingested data points and the calculated ESG metrics — is exposed through a chat interface built for non-technical stakeholders. It answers direct questions and generates visualizations on demand: how much European electricity came from renewable sources last year, which stores offer the biggest opportunity to improve renewable use, which country most of the silk is sourced from, who the top US ready-to-wear suppliers are.

The first ESG report, built in-house, on deadline.

The platform extracted ESG data across more than 400 stores and 2,000 suppliers worldwide, hit 99%+ extraction accuracy on validated data points, and gave every calculated KPI a full audit trail back to its source document. That combination let the client accelerate its first consolidated ESG report and meet a strict legal deadline, without paying for an outsourced consultancy to do the work — while the chat interface put the underlying insights within reach of anyone who needed them, not just the data team.