AI Agents & Workflows for Accounting, Legal and Consulting Firms
Billable hours go into first-pass review and into finding the answer that already exists somewhere in the firm. We build workflows that do the first pass, cite a source for every position they take, and never let anything reach a client without a qualified professional owning it.
The work we take off the desk
Named processes, not categories. If none of these are your bottleneck, the assessment will say so.
First-pass review priced at associate rates
Someone reads a contract clause by clause against the firm’s standard positions and writes up the deviations. It is necessary, it is repetitive, and it is the least leveraged use of a qualified person’s day.
The answer exists, but finding it costs more than redoing the work
A previous matter solved this exact question. Locating it across the DMS, the precedent bank and someone’s inbox takes longer than drafting from scratch, so the firm drafts from scratch again.
Intake and engagement admin
Conflict checks, engagement letters, KYC document chasing. Non-billable, unavoidable, and consistently the reason a matter starts a week late.
Bookkeeping intake and month-end queries
Receipts and invoices arrive in every format there is. Coding them, spotting duplicates and assembling the client query list is a monthly tax on the practice.
What we actually build
Every step below is a real step in the build. Where a person still decides, it is marked — those gates are designed in, not bolted on.
Contract first-pass review against your playbook
Your playbook already defines the positions. The work is applying it consistently at volume — which is exactly what a deterministic workflow is for.
- 1
Segment and classify every clause
Indemnity, limitation of liability, governing law and jurisdiction, termination, IP, confidentiality, payment terms, assignment. Unclassifiable clauses are surfaced rather than skipped.
- 2
Match each clause against your playbook position
Preferred, acceptable, or unacceptable — using your firm’s own documented positions, not a generic risk model bought off a shelf.
- 3
Draft the deviation memo
The clause as drafted, the position it fails, a risk rating, and the fallback wording your playbook already specifies for that situation.
- 4
Cite the source behind every position
Each assertion links to the playbook paragraph it came from. A position with no citable source is not asserted — it is flagged as outside the playbook.
A qualified fee earner reviews and owns the output
Human decidesThe workflow produces a first pass for a professional to work from. It does not produce advice, and nothing reaches a client automatically.
Precedent & authority retrieval
Deciding where to look, and knowing when the firm’s material genuinely does not answer the question, is judgement work. That makes it an agent.
- 1
Interpret the question and choose where to search
Matter files, precedent bank, firm knowhow, published sources — selected per question rather than searching everything every time.
- 2
Retrieve and rank candidate passages
Ranked on relevance and on how current the source is, since a superseded precedent is worse than no precedent.
- 3
Answer with a citation on every proposition
Each statement links to the paragraph that supports it, so verification is a click rather than a research task of its own.
- 4
Decline when the material does not support an answer
Explicitly designed to say "the firm’s material does not cover this" instead of producing fluent text to fill the gap. This is the single most important behaviour in the whole build.
- 5
Log the question and the sources used
Over time this shows the knowhow team what the firm keeps re-asking — which is a map of the precedents worth writing.
Bookkeeping intake & coding
High volume, low ambiguity, and the coding history to learn from is already sitting in the ledger.
- 1
Classify and extract
Supplier, date, net and tax amounts, currency, document type.
- 2
Propose the account code from this client’s own history
Coding conventions differ between clients. The proposal comes from how this client has been coded before, not from a generic chart.
- 3
Flag duplicates and out-of-policy items
Same supplier, same amount, same week. Categories outside the agreed policy. Missing tax documentation.
Post the confident items, queue the rest with a reason
Human decidesThe queue states why each item stopped, so clearing it is a decision rather than an investigation.
- 5
Assemble the month-end query list as one message
Clients answer a single consolidated list far more reliably than a month of individual chasers.
How you will know it worked
We are a young practice and we do not have a wall of client logos to point at. So instead of asking you to trust results you cannot check, here is exactly how the result gets measured on your data — and how you check it yourself.
The metric is agreed before anything is built
You and we write down what is being measured and what counts as good, in advance. If we cannot agree a measurable definition, that is a signal the process is not ready to automate — and we would rather find that out in week one.
The baseline comes from your records, not ours
The "before" figure is drawn from your own system logs for the period preceding go-live. No industry benchmark, no vendor-supplied comparison, no number we brought with us.
Measurement runs in production, on your data
Live operation over an agreed window, against the documents and cases you actually receive. Not a curated test set, and not a demo environment where the inputs were chosen by us.
You get the raw log, not a summary
Per-item results including every case the workflow got wrong and why it went wrong. You can recompute our headline number yourself, and we would rather you did.
The result is reported either way
Including when it falls short of the target we agreed. A supplier who only reports the wins is not measuring anything — they are selecting. You will see the misses in the same document as the hits.
It runs inside the systems you already have
Nobody logs into a new tool. Where an API exists we use it; where one does not, we use supervised UI automation against the same screens your staff use — and we tell you which is which before you commit.
How a build runs
Discovery
We sit with the people doing the work and map the process as it actually runs, including the exceptions nobody wrote down. We come back with a shortlist of candidates ranked by volume, error cost and how cleanly they can be automated.
Pilot
One workflow, built end to end and put into production against your live systems. We agree an accuracy target up front and measure against your data, not a benchmark set. If it misses, you see the number.
Deploy
Integration hardening, access control, audit logging and the human escalation paths. Your team is trained on the runbook and owns the operating procedure before we step back.
Operate & extend
Monitoring, drift review and tuning as your documents and edge cases change. Once one workflow is trusted, the next one costs far less than the first.
Start with one workflow
Not a platform rollout and not a strategy deck. One process, in production, measured on your own data — so the decision to do the next one is made on evidence.
What the pilot includes
- Discovery workshop: we map the process as it actually runs, not as the SOP describes it
- One workflow built end to end and integrated with your live systems
- An accuracy baseline measured on your own documents and data, published to you
- Handover documentation and an operating runbook your team owns
- 30 days of tuning after go-live
Built on our own stack
We are not assembling someone else's components. The engines underneath these workflows are the products we already build and run.
AI Knowledge Base
Retrieval grounded in your own precedent bank and playbooks, deployed privately, with citation back to the source paragraph on every answer.
Learn moreAIGC Engine
Drafting in the firm’s house style for memos, engagement letters and client updates.
Learn moreIT Consultancy & Integration
DMS and practice management integration, access control mapped to your matter permissions, and retention rules that satisfy your regulator.
Learn moreProfessional Services: common questions
Will client-confidential material be used to train a model?
No. We deploy privately, your material stays inside your environment, and nothing from your matters is used to train models we deploy for anyone else. Where a hosted model is used for a specific step, we tell you which step, which provider, and what leaves your boundary — before you sign anything.
How do you stop it inventing an authority?
Three mechanisms, not one. Answers are retrieval-grounded, so the system can only assert what it can retrieve. Every proposition must carry a citation, and anything it cannot cite is not asserted. And the retrieval agent is built to decline explicitly when the firm’s material does not cover the question. A qualified fee earner still signs off on everything that leaves the firm.
Who is professionally responsible for the output?
Your fee earner, always. These workflows produce a first pass to work from, not advice. We build the human sign-off step into the workflow itself so it cannot be skipped by configuration, and we log who approved what.
Do we have to reorganise our precedent bank first?
No. We work with the material as it is, including inconsistent naming and duplicated versions. Output quality does track the quality of the underlying material though, and discovery will tell you honestly where the gaps are — which is often useful in itself.
What does a pilot actually deliver?
One workflow in production in 4-6 weeks, measured against a target you agree up front on your own documents. Contract first-pass review is the usual starting point for legal practices; bookkeeping intake for accounting practices.
Tell us the process that hurts most
The assessment is a working session, not a pitch. If the honest answer is that your bottleneck is not worth automating yet, that is the answer you will get.