AI strategy, transformation, and fluency, with governance and evals built in.See the full operating read →
An enterprise financial-services analysis function
Raw P&Ls To Senior-Approved Analysis, Eval-Checked
An agentic financial-analysis harness that takes raw P&Ls to senior-approved analysis, with an eval trust-layer and an adversarial reviewer enforcing accuracy, PII-safety and authorization on every run.
The proof
The number, kept honest.
01
The challenge.
Analysts produce analysis documents from raw P&Ls inside a permissioned, collaborative hierarchy. They needed AI speed without losing governance: every output had to be accurate, free of PII leakage, and authorized for the person requesting it. In a regulated function, an ungoverned generation is a liability, not a shortcut.
02
The approach.
Governed-context RAG over the firm’s data and P&Ls feeding pre-vetted analysis templates, with multi-model agentic generation (Claude primary, routed per use case).
An eval trust-layer that enforces accuracy, PII-safety and enterprise authorization on every single run — not a post-hoc audit.
A maker-checker adversarial review where an independent model flags inconsistencies before sign-off, plus in-document highlight → query → resolve and senior approval inside permissioned spaces.
03
What shipped.
A built financial-analysis harness: governed-context RAG, templated multi-model generation, the per-run eval trust-layer, the adversarial maker-checker reviewer, and the in-document review/approval workflow.
AI built across the board
Start with the AI work that moves the number. Keep the proof built in.
Start with Strategy, Transformation, or Fluency; use Quick Audit when the first need is an independent read on what is already running.