AI systems for firms whose most expensive people spend their day on admin
In a professional services firm, the constraint is billable hours, and a surprising share of them go to work no client would ever pay for: chasing documents, re-typing intake details, assembling reports, writing the same follow-up email. That is the work these systems take.
Where the money leaks
Intake is a week of email tag
A new client needs details, documents, ID and an engagement letter. Collected by email, that takes a week and three reminders, and it happens before a minute of billable work.
Document chasing is a full-time job
Missing statements, unsigned forms, the one page nobody sent. Somebody senior usually ends up doing the chasing, which is the most expensive way to do it.
The same answers, written again
Status updates, scope questions, deadline reminders, onboarding explanations. Every firm answers the same forty questions forever, from scratch, individually.
Nobody can see utilisation until month end
Hours, matters, capacity and pipeline live in separate tools. By the time the picture is assembled, the month you could have fixed is over.
Accounting and bookkeeping
Season is a document problem. The bottleneck is rarely the work, it is getting complete, correct information from every client before the deadline. Structured intake plus automatic chasing turns that from a scramble into a process.
Documents that read themselves. Statements, receipts and forms arrive in every format imaginable. An AI layer extracts the fields and flags what is ambiguous instead of a junior re-keying it.
Deadlines that manage themselves. Filing dates, instalments and renewals tracked per client, with the reminders going out on their own.
Client document collection
A per-client checklist that requests exactly what is missing and keeps chasing until it arrives, without a person writing the reminder.
Document parsing and extraction
Statements, receipts and forms read automatically into structured records, with anything unclear flagged for a human rather than guessed.
Deadline tracking
Filing and instalment dates monitored per client, with escalating reminders as the date approaches.
Is it safe to run client financial data through an AI layer?
Does it replace our accounting software?
Legal and advisory
Intake and conflict checks. New matter details captured in one structured pass, with the routine checks run automatically before anyone spends time on the file.
Engagement paperwork on rails. Letters generated from the matter record, sent, chased and filed, instead of drafted from a template someone copies each time.
Status updates without the phone call. Clients ask where things stand because they cannot see it. Scheduled updates remove most of those calls, and the ones that remain are worth having.
Matter intake
Structured capture of the details a new matter needs, routed by type and urgency, so nothing starts on a partial picture.
Engagement and signature workflows
Documents generated from real data, sent for signature, chased and filed automatically.
Client status updates
Scheduled, accurate progress updates generated from the matter record rather than written by hand.
We cannot let a system give legal advice. Does that rule this out?
What about confidentiality?
Consultancies and agencies
Proposals that go out the same day. Structured intake plus generated first-draft scoping means the proposal lands while the prospect still remembers the call.
Onboarding that runs identically every time. Kickoff, access, questionnaires and the first reporting cycle sequenced rather than remembered.
Reporting that assembles itself. Client-facing reports built from the systems that hold the data, on a schedule, instead of a junior rebuilding decks every month.
Proposal and scoping drafts
A structured brief in, a first-draft scope out, ready for a human to edit rather than write from nothing.
Client onboarding sequences
Kickoff, access, questionnaires and first reporting cycle delivered the same way for every client.
Automated client reporting
Recurring reports generated from live data and delivered on schedule, with commentary left to the human who has something to say.
Will automated reports make our work look commoditised?
Can it work with the tools our clients use rather than ours?
What a first build usually looks like
In professional services the first build is almost always intake or document collection, because both are frequent, mechanical, and sit in front of billable work.
A focused build ships in one to two weeks. Wider programmes covering matter tracking, reporting and a utilisation dashboard run three to four weeks, phased so something is saving time early.
Everything is wired into the practice management, accounting or project tools you already run. You own it, and the documentation is written for your team.
Regulated data, professional obligations
Professional services firms hold some of the most sensitive information there is: financial records, identity documents, health details, matters under privilege.
Loi 25 sets the baseline in Québec, and it is stricter than most firms assume: meaningful consent, stated purposes, bounded retention, and transparency where a decision is made by a system rather than a person. On top of that sit your own professional obligations, which are usually stricter still.
We treat both as design constraints rather than a compliance review at the end. The detail is in the Law 25 and AI guide.
Why Automatik
Built for your stack
Not a generic bot, the system is wired into the tools your business already runs.
You own the system
Full access, full documentation. No platform hostage-taking.
Bilingual by default
Customer-facing pieces work in French and English from day one.
Loi 25 compliant by design
Consent, transparency and data-handling designed in, not bolted on.