If your firm's product is people reading, analyzing, drafting, and advising over documents, you're sitting on one of the highest-ROI AI opportunities there is — and one of the highest-stakes. Truvisory® ships bounded, privacy-preserving AI over your own documents in 90 days, with verification built into the workflow. Not a public chatbot.
Contracts, briefs, workpapers, tax documents, transcripts, past deliverables — the raw material of your work is precisely the data that language models and retrieval-augmented generation handle well. The gap between expectation and readiness is the opportunity: most firms know AI matters and haven't shipped anything yet, and the ones pulling ahead aren't the ones with the most tools — they're the ones with a strategy who shipped one workflow. You already know which tasks eat junior hours. Those are your AI candidates.
// The efficiency gain is real only when human verification is built into the workflow, not bolted on after — that's the architecture we ship, not a public chatbot.
A retrieval assistant grounded in your firm’s own precedents, workpapers, and past deliverables — the highest-ROI, lowest-risk place to start, where the model retrieves from material you trust and a professional verifies the output.
Contract and due-diligence review for law firms, structured extraction from W-2s, 1099s, and K-1s for accounting firms — the work that eats junior hours, with verification built into the workflow rather than bolted on after.
First-draft briefs, memos, proposals, and deliverables, plus grounded research over case law, the tax code, or your own engagements. AI reliably makes professionals faster; a human owns the quality and the citation check.
Bounded, human-in-the-loop, privacy-preserving AI over your own documents — not a public chatbot that trains on client data. The architecture that satisfies your duties of confidentiality and competence, and clears IRC §7216 and the AICPA confidentiality rule.
Professional services is high-ROI and high-stakes at once. Purpose-built legal tools still hallucinate on 17–33% of hard queries, courts are sanctioning fabricated citations, and confidentiality duties bite hard — so the efficiency gain is real only when verification is built into the workflow, not bolted on after. That's the architecture we ship.
Pasting a client's data into a public model is a malpractice-grade risk. We architect around the profession's actual obligations from the first line of code — which is why the deployment is private, grounded in your own documents, and built so a professional verifies every output.
IRC §7216 is a criminal statute for tax-return information, and the AICPA Confidential Client Information Rule reaches all non-public client data. Private deployments with no model training on your data are the architecture that satisfies them.
Purpose-built legal tools still err on 17–33% of hard queries, and courts are imposing per-attorney fines for fabricated citations. Verification is built into the workflow so a professional checks every proposition and citation before it leaves the firm.
Billing the old number of hours for AI-accelerated work is hard to defend. The firms that handle this well — typically $10M–$100M founder-led operators with less legacy-comp inertia — treat AI efficiency as a pricing question, not just a tooling one.
A firm that bills by the hour shouldn't buy AI on an open-ended retainer — fixed scope is the same discipline this site argues for in your own pricing. Most engagements open with a fixed-fee AI Audit, then move into a fixed-scope sprint or an embedded monthly model, with the honest range stated up front.
A process audit across your document, research, and drafting 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 — an internal knowledge assistant over your own documents, or document review and extraction — built private and human-in-the-loop, with a 30-day handover window. A working system, not a prototype.
A capped-hour monthly engagement for firms that want senior AI architecture without an FTE hire — weekly working time plus a monthly architecture review, no retainer trap. The same fixed-scope discipline this site argues for over hourly billing.
Not sure where to start? Take the 1-min AI Readiness Scorecard →
Where AI pays off by discipline, the billable-hour math, the 17–33% hallucination problem, the confidentiality duties, and where a mid-market firm starts. The full research piece, no booking required.
The thinking behind the build — the deep dive on AI by discipline, why mid-market pilots stall, and why we price fixed-fee rather than by the hour.
A working system in production, not a strategy deck — typically an internal knowledge assistant over your own precedents or workpapers, or document review and extraction, built and shipped in 90 days. We baseline current time and cost first, then deploy with verification built into the workflow.
A document-review assistant with verification built in — the most common first workflow — generally reaches production within 90 days. In a Ship-It Sprint that means four to six weeks to ship one workflow grounded in your own precedents or workpapers; a two-week AI Audit can precede it when you want the prioritized backlog and time-and-cost baseline before committing to the build.
With a private, grounded deployment over your own documents — never a public chatbot that may train on client data and breach privilege, violate the criminal statute IRC §7216, or run afoul of the AICPA confidentiality rule. We build on a Cloudflare-native stack you can audit, with no model training on your client data.
For most firms, build over your own corpus. A knowledge assistant grounded in your precedents, workpapers, and prior deliverables is usually the strongest first project, and holding out for a point solution to fit how your firm actually works rarely pays off. Whichever way the build-vs-buy call lands on a given workflow, verification stays in the loop.
Start with the article when you’re still deciding where AI fits — it walks through the use cases by discipline, the billable-hour tension, and the professional duties. Come to this page once you’re ready to put a verified, private assistant in front of your team. Read the guide first, then book the scoping call.
// Other industry practices — Real estate · Financial services · Healthcare · Field service · E-commerce
Bring one workflow you want to ship — a knowledge assistant over your precedents, contract and due-diligence review, or tax-document intake and extraction — with verification in the loop. We come with a working hypothesis, a stack pick, and a fixed-scope ballpark. No SDR, no drip.
