Move AI into the work that changes the P&L.
Use the AI Audit to pick the workflows where AI can change revenue, margin, or cycle time, then ship the operating playbook and reporting trail your team can keep using.
Most AI work stalls in side projects. We focus the transformation pass on critical workflows, measurable deltas, and PE-ready evidence.
Highest-leverage workflows, by sector.
The six finance sub-segments where TrustEvals operates. Each pattern below is a starting catalogue, not a closed list.
| Phase | Window | What lands |
|---|---|---|
| Phase A1 | Week 1–2 | Discovery + governance foundation. Shadow MCP add-on optional. |
| Phase A2 | Week 3–5 | Vendor evaluation + per-vendor scorecards. |
| Phase A3 | Week 5–8 | PoC and validation against the priority workflows. |
| Phase A4 | Week 8–10 | Rollout, training, board-ready reporting in place. |
Module A. Ten weeks. Two priority tool categories.
Indicative for scaled financial-services and fintech portfolio companies. Smaller engagements compress; enterprise-wide engagements scale across additional teams and workflows. Scope is sized to your environment after the AI Audit.
Module B adds two more tool categories. Both modules can run concurrently in 10 weeks.
Start with the AI Audit →Test readiness for real process delta.
The AI Transformation Scorecard is the quick diagnostic for whether a workflow is ready to move from pilot motion into value capture.
PE portcos moving AI into operations.
Financial-services and fintech portfolio companies need one path to evaluate, govern, and deploy AI at scale, with reporting fit for executives, boards, sponsors, and FS supervisory review.
Module A covers enterprise chat and developer AI tooling. Module B adds enterprise search and customer-experience automation. Shadow MCP Discovery extends the Phase A1 audit to AI paths DLP and CASB miss.
Real estate transformation runs under NDA.
The pattern: NOI-anchored use cases (leasing, CapEx procurement, predictive maintenance, smart building, parking, ESG) framed against a per-property NOI delta, with the data architecture and governance work that makes the delta measurable.
We build what the workflow requires.
AI Transformation is hands-on implementation: agents, workflow plumbing, evals, observability, and handover. The constraint is scope and measurement, not whether the system includes agents.
Agents and workflow code
We build or refactor agents when the Audit identifies a finance workflow worth shipping.
Evals and observability
Trace capture, eval pipelines, workflow metrics, and exception routing are part of the implementation.
Value and risk together
The workflow ships with business outcome measures and the controls needed to defend the change.
Method transfer
Fixed-scope deliverables, owners, runbooks, and measurement patterns transfer to the customer team.
Capture-side workstream, anchored on the AI Audit.
Start with the 2-week AI Audit.
Leave with the operating read: AI value, AI risk, fluency gaps, owners, and the next funded workstream.
Common questions, direct answers.
Single workflow is fine. Module A's Phase A1 includes prioritization, so we tell you which workflow to start with based on data.
Then we skip Phase A2 vendor eval and accelerate into PoC + rollout. Engagement compresses to ~6 weeks.
Every AI Transformation deliverable includes the Value-Capture Report Template, built to be investor-ready, designed for ongoing population by your team.