Industries · Professional Services
AI that runs on live client work, not in a strategy deck
Banao builds and deploys AI inside professional-services firms — document review, contract analysis, knowledge retrieval, proposal drafting, and time-and-billing — for law firms, accounting practices, consultancies, and advisory shops.
Every system below runs on live engagements, wired into your DMS, practice-management, and billing tools. We sell deployed workflows, not a prompt library.
A 50-lawyer disputes practice— first-pass document review on live discovery, every call traceable to its source page.
The first call is free · 45 minutes · no obligation
What we build
What we deploy in professional-services firms
Each of these maps to either a billable hour you're losing or non-billable time you're paying for. We start where the leakage is measurable.
Document review & due diligence
First-pass review across discovery sets, data rooms, and disclosure bundles — ranked by relevance and privilege risk, with every decision linked to the source page for sign-off.
Contract analysis & abstraction
Clause extraction, deviation flagging against your own playbook, and obligation tracking across a contract portfolio, so renewals and risks stop hiding in PDFs.
Knowledge retrieval
A chat-queryable layer over your past matters, memos, and precedents — answers cited to the original file, so juniors stop re-asking partners and rebuilding old work.
Proposal & pitch drafting
First drafts of proposals, RFP responses, and engagement letters assembled from your own winning material, leaving the fee-earner to edit rather than start cold.
Time capture & billing narratives
Passive timekeeping from calendar, email, and document activity, with draft narratives prepared for review — never auto-sent — so recorded time matches the work done.
Client intake & conflict checks
Structured intake from inbound enquiries, automated conflict screening, and matter setup routed to the right team — before unbillable admin piles up.
Receipts
Deployed on live engagements
Metrics shown dotted (··) are being finalised in our case-study metrics pack. The deployments are live; we will not publish a number before it is verified. Client names are withheld where confidentiality terms require it.
First-pass document review on live discovery
A litigation practice ran first-level document review on associate hours — expensive, slow, and inconsistent between reviewers. Banao deployed a review model over their discovery sets that ranks documents by relevance and privilege risk and links every decision to the source page, so a partner signs off on the exceptions instead of reading the whole set.
A decade of past engagements made searchable
Years of memos, working papers, and engagement files sat in folders no one could search. Banao built a retrieval layer over the firm's own document store so staff ask a question in plain language and get an answer cited to the original file — instead of re-asking a partner or rebuilding work that already exists.
Dogfooding
We run our own services firm on the AI we sell
Banao is itself a ~300-person professional-services firm. We win work on proposals, staff it from a shared bench, and bill it — and every workflow on this page runs against our own engagements before a client sees it.
InterviewGod screens our own engineering hires. Vikaas runs our own demand generation and proposal pipeline. A firm that lives on billable hours is a harder test for billing and knowledge AI than any demo environment — by the time a system reaches your firm, it has already survived ours.
Screens Banao's own engineering hires every week.
Runs Banao's own demand-gen and proposal pipeline end to end.
The honest version
When AI doesn't earn its keep in a firm
Most vendors will sell you a model regardless. We would rather tell you when not to build — it is why managing partners take our second call.
- Low matter volume: if a workflow runs a handful of times a month, a paralegal or analyst is cheaper than a trained pipeline. We'll say so.
- Judgement that can't be delegated: AI drafts, ranks, and retrieves — it does not give the advice a client is paying a partner for. We scope it as first-pass, with a human signing every output.
- Hard confidentiality boundaries: if matter data cannot leave a specific environment, week one is deployment architecture inside your walls, not modelling.
How we start
How we start — fixed-price, low risk
You have been pitched AI by every legal-tech booth and vendor already. We start by proving where the hours actually leak, not by quoting a build.
- 01
AI Discovery Sprint
2 weeks · fixed price
We sit with your fee-earners and ops team, map where billable and non-billable hours go, and hand back a ranked list of AI opportunities with baseline ROI maths and a go/no-go per item — yours to keep either way. If you proceed, the Sprint cost is credited against the build.
- 02
Build
Security and data first, then the workflow. We integrate with your DMS, practice-management, and billing systems, and tune models on your own precedents and playbooks rather than a generic corpus.
- 03
Production & adoption
Roll-out with human sign-off built in, plus the change management fee-earners need to trust it. The system keeps improving as it sees more of your matters.
FAQ
Frequently asked questions
Our matter data is confidential. Where does it go?
It stays inside a boundary you approve — your cloud tenant or an isolated environment we stand up for you. We do not train shared models on your matter data, and access is scoped to your firm. Deployment architecture is agreed in week one, before any document is touched.
Will AI give legal or financial advice to our clients?
No. Every workflow is scoped as first-pass: it drafts, ranks, retrieves, and flags, and a qualified fee-earner reviews and signs every output. The advice your client pays for stays with your people; the AI removes the grind around it.
We bill by the hour. Won't automating work cut our revenue?
It shifts hours, it does not erase them. The work AI takes off your desk is mostly non-billable or write-off time — review, admin, search, timekeeping. Fee-earners get those hours back for billable judgement, and passive time capture tends to recover billables that were quietly going unrecorded.
How do we prove ROI before committing budget?
That is what the AI Discovery Sprint produces — fixed price, two weeks, you keep the ROI model whether or not you continue. Worst case you have an independent assessment of where your hours leak; best case you have the business case your partners need to approve a build.
How fast can a workflow reach our fee-earners?
A typical path is a 2-week Sprint, a 6–8 week build, and a 4-week rollout with adoption support. Banao's ~300-engineer bench means delivery starts in weeks, not the months a lateral hire or a single contractor would take.
Get started
Find out where the billable hours actually leak
Bring your most painful document, intake, or billing bottleneck. In 45 minutes we'll map the AI opportunity and the ROI maths behind it.
Book a Discovery Sprint