Pulling sustainability figures out of reports
financial group reporting on sustainability · Gulf
The shape of this problem
A human reads it and types it in again
This is one of our own builds, not a client engagement. It is capability evidence and it is described as such.
The problem
Analysts needed comparable environmental, social, and governance information out of long, inconsistently structured reports and scanned documents. Comparability is the hard part. Every issuer reports on its own template, with metrics in tables that differ in units, scope, and reporting period, and some of it exists only as a scan. Most of an analyst's review is therefore spent establishing what a given number actually refers to, before any comparison is possible.
What we built
We implemented a pipeline that ingested PDFs and images, extracted text and metadata, identified ESG concepts and metrics, linked each piece of evidence to its source page, and presented both document-level and portfolio-level comparisons.
What moved
| Measure | Before | After |
|---|---|---|
| ESG report-review time | † | down 65% |
| Extraction completeness | † | up 30% |
| Documents reviewed per analyst | † | up 45% |
† Measured against the prior level of the same measure. The source publishes the size of the movement, not the figure it moved from.
ESG report-review time
Measured against the client's own prior process, indexed to 100. The source publishes the size of the movement, not the absolute figure it moved from.
Extraction completeness
Measured against the client's own prior process, indexed to 100. The source publishes the size of the movement, not the absolute figure it moved from.
Documents reviewed per analyst
Measured against the client's own prior process, indexed to 100. The source publishes the size of the movement, not the absolute figure it moved from.
Figures are drawn from the practice's own delivery records for the engagement named, measured against the process that preceded it. They have not been through third-party audit, and none is presented as an average across clients.
What it turned on
The evidence boundary held throughout - raw values and source pages were never overwritten by normalised outputs, and a missing disclosure was never silently converted into a zero or an inferred commitment. That specific failure is what makes most ESG analytics untrustworthy, and avoiding it is what makes the throughput figure meaningful.
- Service line
- AI Document Intelligence
The proof is telecom and financial-services documents, not a construction subcontractor invoice. The machinery is identical; say which it was.
Start here
Which of the four is yours?
Tell us the documents and the monthly volume and we will send the two closest records, with the proof behind each and the honest note where the match is partial.
You get a reply within one working day, from the engineer who would do the work - not a sales sequence.