Turn AI into an operating plan finance can defend.
Finance teams need a defensible read on where AI is already changing work, where it is creating risk, and which workflow deserves the next dollar. The AI Audit gives that read; services close the gap by transforming the workflow, building the evidence, or lifting the team.
Two-week first read. Follow-on work is sized to the gap, not packaged as one bundle.
One read first. Then the right workstream.
The Audit separates strategy from transformation, current state from steady state, governance gaps from measurement evidence, and opportunity from shadow-AI risk. Evals sits underneath every workstream as the measurement layer.
Most engagements start with the AI Audit.
The Audit maps approved tools, shadow AI, embedded features, internal agents, spend, and workflow readiness. The output is the operating read: current state, steady state, governance gaps, opportunity map, risks, and the next move.
Audit feeds the workstreams. You don’t run everything.
Most teams run one or two workstreams after the Audit. The operating read decides the order.
The sequencing question is simple: are we choosing the strategic bet, transforming a workflow, building the evidence layer, or helping people use AI well in the work?
Four 8-minute scorecards. One per decision area.
Take the one closest to where you're stuck. Each scorecard turns the fuzzy AI question into a small set of decisions a board can act on.
The AI Adoption Scorecard is the upstream sequencing instrument used in the PE outbound sequence: Strategy × Fluency plus four diagnostic questions a board can act on. Scorecards are diagnostics, not the public service architecture.
Four spaces. One methodology.
Each tile links to the deep version on the relevant service or industry page.
Route by buyer shape.
| Buyer shape | Best entry point |
|---|---|
| PE Operating Partner | Industries · Private Equity → |
| CEO / Board (single firm) | Solutions · CEO → |
| CIO / CAIO | Solutions · CIO → |
| CFO | Solutions · CFO → |
| CISO | Solutions · CISO → |
| AI-native finance product team (production launch) | Side track · Product AI → |
| AI-native finance product company (evals need) | Measurement layer · Evals → |
| Industry-led search (PE / Banks / Fintech / REITs / Insurance) | Industries → |
Hands-on. Fixed-scope. Platform-anchored.
A named TrustEvals practitioner embeds with your team for the engagement window. We harden the measurement layer where it matters: eval pipelines, trace evidence, observability, and owner review, then hand the operating loop to your team. The operating view keeps improving across engagements.
Start with the 2-week AI Audit.
Leave with the operating read: AI value, AI risk, fluency gaps, owners, and the next funded workstream.
What gets asked every week.
No. The AI Audit is the entry read. It gives the current state, the steady state, the governance gaps, and the opportunity map before we sequence any workstream.
No. Most teams start with the Audit, then run one or two workstreams. The point is sequencing AI Transformation, AI Governance, and AI Fluency from evidence, not buying every workstream.
We complement consulting firms. TrustEvals makes AI recommendations measurable, gives the engagement a current operating read, and keeps the evidence loop live after the strategy work.
The platform is the product. Services come in when a customer needs a faster baseline, deeper architecture work, or method transfer around a specific operating problem. We scope services to the work the evidence justifies, often starting with the AI Audit, then hand the operating loop back to your team.