Private AI for accounting and tax firms
Most of what a client asks is already answered in a memo or in last year's file. AI running on your own server finds it and drafts the reply, without a single payroll record leaving the office.
An accounting practice lives on answering many similar questions quickly, using highly sensitive third-party documentation. Private AI indexes your memos, files and internal criteria and answers with the source cited, and it takes the repeated questions off the team. And because it runs on your own server, payroll, filings and your clients' employees' data are never transferred to an outside provider.
The real pains
All of them get worse in filing season.
The same question, forty times
"What do I need to register a new contractor?" Already answered in writing, still answered by hand every single time.
The know-how lives in two heads
How you handle a specific case is something the partners know. If they're busy or away, the file stalls.
Season means everyone is blocked
Year-end, quarterly filings, tax returns: the work that could be automated is exactly what multiplies in those weeks.
A huge archive searchable only by filename
Thousands of client files in folders by year, and the only way to find something is remembering where it was.
What AI does about those four
Answers frequent questions in your own words
The answer comes from your memos and internal notes, not from generic web text, and cites the document behind it.
Puts internal criteria within reach of the whole team
What used to require asking a partner becomes searchable, with the actual precedent in front of you.
Takes the peak-season spike
In those weeks the bottleneck isn't the calculation, it's the questions and hunting down the paperwork each filing needs. That gets resolved in seconds, without interrupting a colleague.
Searches the archive by content
"Clients we applied this treatment to last year" returns the files, even if nobody ever tagged them that way.
The data isn't yours
An accounting practice doesn't only handle its own data: it handles payroll, filings and personal data belonging to its clients' employees. There you act as a processor, and putting that documentation into a cloud tool turns the AI provider into one more sub-processor to document, disclose and assess.
With private AI that chain disappears: the model runs on a server in your office and no document leaves the network. Less surface to audit, and a simple answer when a client asks where their data ends up.
What it does not do
It does not file returns or replace your tax software: it computes no liabilities and signs nothing with the tax authority. It gives no opinion of its own: it retrieves and drafts from what you wrote, and the adviser's review remains mandatory. And it is not aware of a reform you never indexed: keeping the rules current is still your job, through your own memos.
Before you ask
Is it up to date with the latest tax reform?
Only with what you index. A generic model has frozen, outdated knowledge, which is why answers are built on your own memos and internal notes, the ones you actually keep current. If a memo is from 2024, the AI says so and cites the date.
What about the personal data of our clients' employees?
That is exactly why the private approach fits. On payroll work you are a processor handling third parties' data. With the server in your office, that data is never transferred to an AI provider, so there is no sub-processor to document and no international transfer to assess.
How long until something is running?
A pilot scoped to one area (payroll only, for instance) with a few hundred documents is typically live in weeks.
Let's start with one area
A 30-minute call to pick which part of the practice to begin with.