Your firm runs the same loop all day — intake a document, extract the data, review it, communicate. Truvisory® ships the AI that handles the document load — loan files, submissions, KYC, internal knowledge — in 90 days. Bounded, auditable, human-in-the-loop, and built for the most regulated corner of the economy.
A loan file is 30 to 50 documents. A claim is a stack of forms, photos, and PDFs. An RIA's value is locked inside meeting notes and a CRM. Historically all of that required a person to read, key, and route it — and that's precisely the work intelligent document processing, RAG, and intake automation now handle. The constraint isn't model quality; it's data readiness and getting one workflow past the pilot. That's what we ship.
// Industry-wide figures are ceilings contingent on data and execution. Treat any single vendor number as marketing until measured against your own baseline.
This is the most heavily regulated corner of the economy, and the regulators have already moved on AI. So auditability and human review aren't a hedge — they're the deployment posture: prompt and output logs treated as books-and-records, access controls, and model governance, with no autonomous black-box decisions on credit or claims and no-training protections on customer data.
The SEC's first AI-washing cases settled for $400K total — never market AI you aren't actually using.
AI-generated client content is a firm communication, and prompt and output logs are treated as records.
Models must be auditable, and a vendor's AI model is your model risk to govern — accountability can't be outsourced.
Adopted in roughly two dozen states — a written program, vendor diligence, and consumer-notice expectations.
Extract data from loan files, KYC documents, and insurance submissions — applications, tax returns, bank statements, ACORD forms — turning manual stare-and-compare data entry into minutes, with a human reviewing every extraction.
A retrieval assistant grounded in your own policies, procedures, and product and regulatory content — the lowest-risk way to keep data inside the firm and get staff answers fast, with a citation to the source for every answer.
Credit-memo and underwriting drafting for lenders, claims and submission intake for insurers, and meeting prep, note-taking, and CRM updates for RIAs — the document and admin load handled so your people keep the judgment and the relationship.
Bounded, human-in-the-loop, and auditable by design — prompt and output logging, access controls, and model governance — because in regulated finance a vendor’s AI model is your model risk to govern. Never autonomous black-box credit or claims decisions.
This is the most regulated vertical you can deploy AI in — SEC AI-washing enforcement, FINRA supervision, banking model-risk guidance, fair-lending law, and the NAIC insurance bulletin all apply. So human-in-the-loop and auditability are the credible default, not a hedge: every output is reviewed, every request is logged, and customer data stays under no-training protections in an architecture you can audit.
Most regulated-finance engagements open with a fixed-fee AI Audit that sizes cost, time, and model-governance gaps, then move into a fixed-scope sprint or an embedded monthly model. The range is on the page — no "request a quote" wall.
A process audit across your document, intake, and review workflows — a prioritized backlog, ROI sizing per opportunity, and a build·buy·partner recommendation you can hand to any team, including ours.
One production-grade workflow shipped end-to-end — loan-file processing or an internal knowledge assistant — built auditable and human-in-the-loop with no-training data protections, and a 30-day handover window. A working system, not a prototype.
A capped-hour monthly engagement for firms that want senior AI architecture and model governance without an FTE hire — weekly working time plus a monthly architecture review, no retainer trap.
Not sure where to start? Take the 1-min AI Readiness Scorecard →
Where AI pays off in banking, wealth management, and insurance, the proof by sub-vertical, the SEC, fair-lending, and model-risk reality, and where a mid-market firm starts — the full research piece, no booking required.
How we think about shipping AI into a regulated firm — the pilots that stall, the warning signs, and why fixed scope beats an open-ended retainer.
A working system in production, not a strategy deck — typically document and process automation like loan-file processing, submission intake, or an internal knowledge assistant, built and shipped in 90 days. We baseline current cost and time first, then deploy with a human reviewing every output and audit logging in place.
A loan-file processing assistant ships in 90 days, not an open-ended pilot. A Ship-It Sprint runs four to six weeks to put one workflow — loan-file or submission processing, or an internal knowledge assistant — into your team’s hands with audit logging in place; a two-week AI Audit comes first if you want the prioritized backlog and ROI sizing before committing to a build.
Everything is bounded, human-in-the-loop, and auditable — prompt and output logging treated as books-and-records, access controls, and model governance — because the regulators have moved on AI-washing, fair lending, and model risk. We never build autonomous black-box credit or claims decisions, and we keep customer data in an architecture you can actually audit, with no-training data protections.
Usually integrate-and-customize, because mature point solutions and core-system vendors already cover much of this — and in regulated finance, buying or partnering tends to outperform internal builds. The catch the third-party guidance makes explicit: a vendor’s AI model becomes your model risk to govern. So whichever path fits, we build the governance, audit logging, and integration around it.
That deep dive is research-grade — it breaks down where AI pays off by sub-vertical, with the proof and the SEC, fair-lending, and model-risk reality spelled out. This page assumes the research is behind you and you want to scope a build. Read AI for banks, RIAs, lenders, and insurers for the evidence, then book a call to act on it.
// Other industry practices — Real estate · Healthcare · Field service · Professional services · E-commerce
Bring one workflow that buries your people in paper — the loan-file intake queue, an insurance submission backlog, or a credit-memo draft that eats an analyst's afternoon. We come with a working hypothesis, a stack pick, and a fixed-scope ballpark. No SDR, no drip.
