AI support desk for law firms
A firm’s clients call to know where their case stands, when the next hearing is, which documents to provide — factual questions that interrupt associates all day. The agent answers from information the firm has validated, and routes every substantive question to the lawyer, without exception.
In your day-to-day
- 01
Answers on the factual state of the case — hearing scheduled, submissions filed, expert assessment underway — as validated by the firm.
- 02
Collection of documents requested from the client, with a list of what is missing and follow-ups until the file is complete.
- 03
Appointment booking with the right lawyer, taking hearings and unavailability into account.
A typical scenario
In a family- and employment-law firm, the front desk picks up thirty times a day — and half the calls boil down to one question: “where does my case stand?”.
- 01
At 7:30 PM a client asks whether her hearing is still on: the agent answers with the date recorded on the file and the list of documents still expected from her.
- 02
Before every appointment it checks the file and chases the client for missing documents — the meeting happens on a complete file.
- 03
“Do I have a chance of winning?”: no improvised answer. The question goes to the lawyer, with the context of the exchange.
What changes
Clients get the facts without waiting for a callback, and the front desk recovers whole stretches without the phone ringing — with not a single substantive question handled by a machine.
Order of magnitude
Working assumptions
- →around thirty calls a day to the front desk
- →60% concern purely factual follow-up
- →4 minutes per call, callbacks included
About 6 front-desk hours a week freed from status questions (30 × 60% × 4 min × 5 days) — returned to case preparation.
Indicative estimate built on average sector assumptions — it gets recalibrated on your actual volumes during scoping.
What eats your days
- →
Fee reminders and requests for payment on account come after the casework — and the firm’s cash flow pays for it every quarter.
- →
Procedural-deadline tracking rests on diaries kept by hand — and one missed deadline engages the firm’s liability.
- →
The firm’s inbox mixes court notifications, opposing counsel’s submissions, client documents and prospect enquiries — everything arrives at the same level.
How it works
- 1
The agent learns your business
It is fed your real sources: FAQ, documentation, ticket history, business rules. It only answers what it can source — no improvising.
- 2
Autonomous resolution, fenced
Recurring requests — tracking, invoices, procedures — are resolved end to end. Anything outside the fence goes to the human queue with a sourced draft reply already written.
- 3
Supervision and continuous improvement
Every conversation is reviewed by our engineers in the first weeks. The autonomous-resolution rate rises as the agent earns reliability — never the other way round.
Typical results
60%
of tickets resolved with no human involved, observed in production
3 min
first response, 24/7
×3
handling capacity for the same team
Orders of magnitude observed in production; your diagnostic sets your own baseline and targets.
Frequently asked questions
Could the agent end up giving a client legal advice?+
No — that is a design prohibition, not a setting. Its scope is strictly factual and administrative: case status, documents, appointments. Any question touching the merits, strategy or prospects of success is handed to the lawyer, with context.
What about professional secrecy?+
The agent runs inside the firm’s environment, with per-matter access walls and full logging. Your data is never used to train third-party models, and hosting is chosen with you — including on-premise if the firm requires it.
Is this the problem eating your team’s time?
Tell us how you work today — 30-minute call, then a free written diagnostic of what this agent would change for you, with numbers.
Get my free diagnosticFree resource
Get the self-assessment grid for your sector
Sales, admin, support, operations: the 20 tasks AI agents already handle in SMEs — with, for each one, the tell-tale sign that your team is concerned.