[ Case study ]
The clinic's intake phone line opened for two hours a day and overflowed constantly. Prospective clients with urgent matters waited days to learn the clinic couldn't help with their issue type, and staff spent mornings triaging voicemails.
CLIENT a community legal-aid clinic — FOCUS Encode the eligibility rules exactly
Representative examplesEvery case study in this library is an illustrative composite of the kind of engagement we deliver — written to show our method and standards, not to name clients.
Funded by a mix of grants and council contracts, the clinic provides free legal help across a defined set of matter types, income bands, and geography. Its intake phone line opens two hours a day because that is what staffing allows, staffed by caseworkers who also carry full caseloads. The people calling are often in distress, frequently unsure whether their problem is even legal, and occasionally in crisis — the clinic's duty of care starts at the first ring, whoever answers it.
The clinic's intake phone line opened for two hours a day and overflowed constantly. Prospective clients with urgent matters waited days to learn the clinic couldn't help with their issue type, and staff spent mornings triaging voicemails.
We proposed an assistant that runs the clinic's actual screening questions in order, applies the published eligibility rules exactly, and states outcomes plainly — no soft rejections, no false hope — while treating crisis phrasing as an interrupt that goes straight to a human callback queue. The rules live in deterministic logic the assistant narrates rather than decides, because eligibility is exact and advice is not ours to give. Overnight screenings become a prioritized morning report with full transcripts, so lawyer hours start where they matter. Everything about the crisis path was tested with the clinic's own people in the room.
Just as important is what we ruled out, and why:
The assistant asks the clinic's actual screening questions in order, applies the published rules, and states outcomes plainly — no soft rejections, no false hope.
Certain phrases and matter types interrupt the flow straight to a human callback queue with urgency framing — tested explicitly.
Overnight screenings become a prioritized morning report with full transcripts, so lawyer hours start where they matter.
Delivered by the systems pod — automation specialist over 6 weeks, with working increments reviewed with the client every week.
Obstacle
In testing, the crisis-detection trigger list missed a phrasing pattern the clinic's social worker recognized instantly — a caller describing fear without naming it.
Handled: We rebuilt the trigger list with her in the room, ran her reworded cases through the suite, and made her additions permanent eval cases.
Obstacle
The eligibility rules produced technically correct answers that landed badly — one matter type sat right on the boundary and the plain 'no' read as a door slammed.
Handled: The clinic wrote the boundary wording themselves; the assistant now states the outcome plainly and adds the referral routes the clinic had always given by phone.
The headline: screening availability, with 63% of eligible matters booked to callback without staff contact in the first month — 2 hrs → 24/7, read from Assistant transcripts plus callback log. A second check: crisis-flagged conversations reaching a human within the hour at 100%.
The morning triage hour turned into a working session on real cases — the queue arrives prioritized, with transcripts, and caseworkers start where the need is sharpest. Callers outside eligibility now learn it in minutes instead of days, and several have written back to thank the clinic for the referral routes the assistant offers. The crisis path is the part staff check first when they audit transcripts; it is also the part they trust most, because they wrote its wording.
The result was read from Assistant transcripts plus callback log against the pre-engagement baseline over the stated window, with a guardrail check on crisis-flagged conversations reaching a human within the hour. Where platform-reported numbers and business outcomes differ, this record says which layer it is quoting.
What we would do differently
We would have tested the crisis path with the clinic's social worker in the room — her rewording of one trigger phrase mattered more than any prompt tuning.
[ Related service ]
[ Related builds ]
45 min 4 minAverage handling time per invoice batch (human review only), measured over the first full month
4 hrs 25 minAverage policy-comparison preparation per client file, verified over 40 files
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