Figures from filings,down to the footnote.
Particula-Finance extracts figures from filings, statements, and decks, including the tables and footnotes where the real numbers hide. Every value is typed and carries a source span. Self-hosted, so material non-public information stays yours.
One job, done to spec.
Here is the spec.
Everything below is work the model handles on its own, with no wrapper, no retry loop, and no second call out to a larger model when it gets stuck.
Figures from filings
Revenue, margins, segment data, and guidance from 10-Ks, statements, and investor decks.
Tables and footnotes
Layout-aware parsing for the places disclosures actually live: multi-level tables, footnotes, and restated comparatives.
A source span on every number
Each value links back to page and line in the source document, so analysts audit the extraction instead of redoing it.
Numbers stay numbers
Typed output with currency, units, and periods normalized. No string soup: figures land in your model ready to compute.
Context, latency, hardware,
and what it takes to run.
The numbers a capacity plan actually needs. Sizing gets reviewed against your traffic before the pilot, and the figures go into the agreement in writing.
From first call to production
without a rewrite.
Three steps, and you keep the weights at the end of them. Nothing about the rollout depends on us staying in the loop afterwards.
- 01
Discovery call
30 minutes, no slides. Your task, your data shape, and the security constraints around it. If this model is the wrong fit, we say so on the call.
- 02
Pilot install
Containerized deployment to staging in your VPC or on-prem, on the same stack as Lumen and Notetaker. The eval harness runs on your data and the numbers go into the pilot agreement.
- 03
Production rollout
Runbook handoff, operator training, and 90 days on call. After that it is yours to operate, no vendor dependency.
Five others share
this runtime.
They run on the same serving stack, the same deployment path, and one API, so licensing a second model adds no operational surface.
“Bring a hundred real examples from your pipeline. We run the model on them live, the harness scores the output in front of you, and you decide with numbers instead of a sales deck.”
Sebastian Mondragon, Founder of Particula Tech