Work & Case Studies

The situation

Research briefs are the firm's quiet bottleneck. Preparing a single brief means a partner or senior associate spending four or more hours searching case law, reading precedents, and assembling the argument structure — supported by paralegals working on research full time. Client work queues behind it, and the most expensive hours in the firm go into document retrieval rather than legal judgment.

What is at stake

Partners bill at the highest rate in the firm. Every hour spent locating precedents is an hour not spent on strategy, client counsel, or new matters. At a typical firm's volume, research alone can consume over $150,000 of senior time per year.

What we build

• ▸A research system with access to the firm's full case-law library that reads a research question in plain language, locates the relevant precedents, and drafts a structured brief with each citation linked to its source.
• ▸A mandatory partner review step: nothing the system produces reaches a client or a court without a named lawyer reading and approving it. The system prepares; the lawyer decides.
• ▸A complete audit trail. Every brief records which sources were consulted and why, so the firm can demonstrate the basis for any document it produces.

How it rolls out

Weeks one and two cover the document library and security review — the firm's case files never leave its own environment. Weeks three to five test drafts against briefs already produced manually, with partners scoring the output blind. By week six the system is in daily use for live matters, with the partner review step as the permanent quality gate.

What to expect

Research paralegals shift to case preparation, where most firms are understaffed. Partners describe the change simply: research stops being a scheduling constraint. The firm expands the system's library itself, using the documentation handed over at delivery.

The situation

The compliance team is the firm's single source of truth for policy questions — and its single point of congestion. Staff email questions about internal policy, regulatory requirements, and procedure; the compliance team searches thousands of documents manually and answers hours later. Regulation prohibits any of this material from leaving the firm's premises, which rules out every cloud product evaluated.

What is at stake

Slow answers delay client onboarding, transaction approvals, and audit responses across the whole firm. The deeper risk is inconsistency: under time pressure, different compliance officers occasionally give different answers to the same question.

What we build

• ▸A private knowledge system installed entirely inside the firm's own building, on its own hardware. Nothing — documents, questions, or answers — ever touches an external network.
• ▸Coverage of all policy and regulatory documents the firm holds. Staff ask questions in plain language, in Arabic or English, and receive a precise answer citing the exact document and page it came from.
• ▸A review dashboard for the compliance team showing what is being asked and answered, so they supervise the system rather than answer each question by hand.

How it rolls out

The first two weeks cover installation and document ingestion inside the firm's premises, with their IT security team observing every step. Weeks three and four are a supervised trial: the compliance team compares the system's answers to their own before any staff access. General rollout comes in week five, department by department, with the compliance team retaining authority to correct or annotate any answer.

What to expect

The compliance team's role changes from answering repetitive questions to supervising answer quality and handling genuinely novel matters. Answer consistency — one question, one answer, one cited source — matters as much to regulated firms as speed.

The situation

One front-desk employee handles every inbound call alongside walk-in patients. During consultations, calls ring out; after hours and on weekends, they go entirely unanswered. Thirty to forty percent of after-hours calls are lost — and each lost call is a patient who books with the clinic next door.

What is at stake

For a private clinic, a missed call is a missed booking, and a missed booking is revenue that does not return. The clinic is effectively closed to new business for two-thirds of every day, while paying for advertising that generates calls nobody answers.

What we build

• ▸An AI receptionist that answers every inbound call immediately, day or night, and speaks naturally with patients in Arabic or English — whichever the caller uses.
• ▸Direct connection to the clinic's appointment calendar: it offers genuinely available times, books the appointment during the call, and sends the patient an SMS confirmation before they hang up.
• ▸Judgment about its own limits: medical questions, emergencies, and unusual requests are passed to staff with a recorded summary, never improvised.

How it rolls out

Week one maps the clinic's booking rules — consultation types, durations, physician schedules, insurance questions. Weeks two and three run the system in parallel: it answers, but staff monitor every call and can step in. Full operation begins in week four, starting with after-hours calls only, then extending to daytime overflow once the clinic is confident in it.

What to expect

The booking increase comes almost entirely from calls that previously went unanswered — evenings, weekends, and times the desk is busy with walk-ins. The front-desk employee handles patients in the building rather than juggling the phone.

The situation

Every supplier invoice — PDFs, scans, photographed paper — is read by a person, checked against purchase orders, and typed into the accounting system. The finance team loses hours each day to this, and the error rate runs around eight percent: wrong amounts, wrong codes, duplicates. Errors surface weeks later as payment disputes and reconciliation work.

What is at stake

Beyond the daily lost hours, errors have a compounding cost: supplier disputes, late-payment penalties, and month-end closes that drag. The team is due to grow with invoice volume — automation is the alternative to a new hire.

What we build

• ▸A processing system that receives invoices in any format, reads them, matches each against its purchase order, and enters verified invoices directly into the company's accounting system.
• ▸A confidence rule: invoices the system is certain about flow straight through; anything unusual — a mismatched amount, an unknown supplier, a possible duplicate — is held for a person to review, with the discrepancy highlighted.
• ▸A complete audit log: every invoice records what was read, what it was matched against, and who approved it.

How it rolls out

Weeks one and two connect the system to the accounting software and train it on historical invoices. Weeks three and four run in shadow mode — the system processes every invoice but a person verifies each entry before posting. Automatic posting is enabled in week five for invoice types where the system has proven itself, expanding from there.

What to expect

Month-end close shortens because reconciliation issues stop accumulating. The planned additional hire is not needed. The finance team's daily involvement becomes reviewing the handful of flagged invoices — the exceptions where human judgment genuinely matters.

The situation

A small support team handles hundreds of tickets a week, and the same questions — order status, returns, product specifications, delivery times — make up the great majority. Average resolution time is 48 hours, customers escalate while waiting, and the team burns out on repetition while genuinely difficult cases sit in the same queue as everything else.

What is at stake

Slow support in online retail translates directly into refund requests, chargebacks, and lost repeat customers. The company faces a choice between growing the support team or changing how routine questions are handled.

What we build

• ▸A support system grounded in the company's actual material: product documents, returns and warranty policies, and live order data — so it answers from facts, not guesses.
• ▸Automatic resolution of routine enquiries: where is my order, how do I return this, does this product fit my use — answered immediately, around the clock, with the relevant policy or order detail cited.
• ▸A clean handover for everything else: when a case needs a person, the agent receives the full history and the customer's details already assembled, instead of starting from scratch.

How it rolls out

Weeks one and two ingest the product library and connect order data. Weeks three and four, the system drafts replies that agents review and send — building an accuracy record before any customer receives an unreviewed answer. From week five it handles routine categories autonomously, with the team monitoring a daily quality sample.

What to expect

Agents work only the cases that need a person — disputes, special orders, complex complaints — and resolution quality on those improves because the queue pressure is gone. The company can scale into new product lines without adding support headcount.

The situation

The founder has proven demand for property investment analysis — clients pay for reports assembled manually over days. What they do not have is a technical co-founder, a development team, or eighteen months to learn to build software. Investors want to see a product, not a spreadsheet service.

What is at stake

Manual delivery caps the business at a handful of clients. Every month without a product is a month competitors can close the gap, and the founder's window with early customers and investors is finite.

What we build

• ▸A complete commercial software product: customer sign-up and accounts, subscription billing, and the analysis engine that turns property data into the investment reports clients already pay for.
• ▸The analysis capability at its core — the system evaluates properties against market data and produces the structured assessment previously built by hand over days, in minutes.
• ▸An operations view for the founder: customers, subscriptions, usage, and revenue in one place, manageable by one person without technical staff.

How it rolls out

Weeks one and two lock the product scope to what customers have already proven they will pay for — nothing speculative. The build runs with the founder reviewing a working version every week and adjusting based on customer feedback. Final weeks cover billing, onboarding, and launch to the existing client list.

What to expect

The founder goes into investor conversations with a live product generating recurring revenue, rather than a service business. Because they own the system outright, subsequent feature development is done at their pace, with their choice of engineers.