For Indian law, audit and accounting firms
AAS builds controlled workflows around the work your firm already does: intake, evidence, drafting, review, chasing and operations. People remain accountable at every material decision.
Where capacity leaks
The opportunity is practical: remove repetitive preparation and chasing, then make exceptions easier for senior people to see and resolve.
Capture the facts, answer routine questions, qualify the opportunity and route it to the right professional before the first response.
Prepare first drafts, summaries, checklists and evidence schedules from the matter or engagement record, with review built into the route.
Track missing documents, unsigned engagements, unpaid invoices, stalled matters and candidate steps, then escalate only what needs attention.
Selected UK evidence
These figures come from AAS finance automation work. They show the operating pattern: machines handle volume; people handle the exceptions that matter.
Unknown transactions narrowed to a focused set for human review across a three-year backlog.
Processed overnight for a UK accountancy practice.
Two days of work became a morning exceptions review.
For 18,000 previously unreconciled transactions.
Scope from prior work
Law and accounting work differ in substance. The operational pattern is shared: capture, prepare, review, release, monitor.
Capture enquiries around the clock, answer approved FAQs, filter poor-fit matters and prepare the first letter for review.
Surface value and likelihood-to-win signals, then assign the right lawyer without losing high-value enquiries.
Build legal documents from the case file so fee-earners review and correct rather than begin from scratch.
Capture scope, deadlines, risk indicators and missing documents before the file reaches a manager or partner.
Request and track evidence, summarise submissions and escalate overdue items or exceptions for human attention.
Match records at scale, orchestrate checklists and present a clean exception queue for professional review.
The next move
A controlled pilot creates evidence before commitment. Each stage answers the question required to justify the next.
Visible volume, delay, cost and a named owner.
Handoffs, exceptions, templates and controls.
Approved rules, parallel run and human review from day one.
Time, quality, response speed and confidence.
Scale only when the evidence supports the next move.
The output is a working pilot and a clear go / no-go decision, not a transformation programme built on assumptions.
Evidence before expansionA focused next step
We will identify where automation can remove cost, delay or missed revenue, then define what a controlled first pilot would need to prove.
Direct enquiry
TO / boris.korol@ai-automation.studio