AI Automation for CPA & Accounting Firms

Client onboarding: from first meeting to signed engagement letter

Onboarding a new client is where firms leak the most goodwill: multiple meetings, notes that live in someone’s head, an engagement letter that takes days to draft, and a document checklist sent as a one-off email. We automate that path end to end — meetings are captured and summarized into a structured record, the engagement letter is drafted from your firm’s own templates and priced scope, the intake form runs itself, and the client gets a live document checklist that follows up automatically.

The partner still reviews and signs everything. The difference is the elapsed time: what took two weeks of back-and-forth compresses into days, and every step of it is on the record instead of in an inbox.

Tax season capacity: the document chase and the data entry

Every CPA knows the tax-season pattern: the work is not the return, it is getting the documents. Staff spend weeks emailing clients for the missing 1099, the brokerage statement, the K-1 that hasn’t arrived — then re-keying whatever finally shows up. It’s manual, it’s repetitive, and it’s the exact thing that caps how many clients a firm can take on.

For a mid-sized accounting practice, we replaced that cycle. An AI-driven intake system chases clients automatically for outstanding documents, reads what comes back — W-2s, 1099s, K-1s, consolidated brokerage statements, each extracted against the schema for its form type — and feeds clean data into the preparer’s workflow. Private-equity fund K-1s, notoriously manual to break apart, are a strong fit: the system pulls the line items and routes anything ambiguous to a human. The result: 84% less time on manual follow-up and 3× more documents processed per staff member, without adding headcount in peak season.

Alongside your staff, not instead of them

Partners are hiring, not looking to cut their teams — and an AI pitch that sounds like “replace your associates” deserves the skepticism it gets. This is built the other way around: the system does the reading, filing, chasing, and first-pass drafting, and your people spend their hours on review, judgment, and the client relationship. The accountant stays in control of every number that ships.

In practice that means the copilot drafts the return and surfaces tax-saving angles and compliance checks; the preparer reviews and decides. Response times improve, error rates drop, and the same team serves more clients — that is the actual unit economics of AI in a firm, and none of it requires anyone to lose their job.

Nothing dropped: engagement status your whole firm can see

After onboarding, the quiet killer is tracking: which documents arrived, what was discussed with whom, which engagement is stuck waiting on the client, which deadline is next. The system keeps that ledger automatically — every document, communication, and status change lands in your practice-management stack, visible to partners and staff alike — so client questions get answered from the record, not from memory, and nothing slips between team members.

When your practice management and tax software will not talk to each other

A lot of firms have good software and still lose hours to it, because the practice management tool and the tax engine were never built to share data. Karbon tracks the work; CCH Axcess or UltraTax prepares the return; nothing moves between them on its own, so a staff member ends up carrying every status update and every document across by hand.

Where a system offers a modern way in, we connect through it. Where an older tax platform does not — and several of the ones firms rely on most, like legacy CCH or Thomson Reuters installs, do not — we build a connector for it or have the automation operate the software the same way a person would. Either way, the firm keeps every tool it already pays for; the manual bridge between them is what goes away.

Security: your stack, your cloud, your controls

It runs behind the tools your firm already uses — QuickBooks, Xero, Hubdoc, document portals and practice-management software — so nobody has to learn a new platform. And because client tax data cannot be handed to an uncontrolled public AI tool, we deploy on infrastructure you control: dedicated model instances via OpenAI, Google Vertex, AWS or Azure, inside your own cloud, with role-based access and full audit logging on every document. Your client data never leaves your environment and never trains a public model — which is also what your FTC Safeguards Rule written security plan will ask of any vendor you bring in.