Intake Triage AI reads every inbound form, call transcript and chat the moment it lands. It scores the case 0–100, flags the statute and the conflict, writes the intake memo, and drops it on the right attorney's desk — before the caller dials the next firm on the search page.
Every firm we look at has the same shape: marketing spend goes up, lead volume goes up, and one or two intake people become the bottleneck that everything upstream is paying for.
Rear-end collision, commercial truck, ER visit, police report, named carrier. This is a $70k fee.
"Thanks, someone will be in touch." The claimant reads it and goes back to the search results page.
Both have an answering service. One of them books a signing appointment for Wednesday.
Forty-one new leads. She reads them in the order they arrived, which is the wrong order.
Voicemail. The case is already signed somewhere else. You still paid for the click.
The on-call attorney gets a push with the summary and a 30-minute SLA clock. The call happens the same night.
Seven weighted factors — practice fit, liability language in the caller's own words, damages severity, statute runway, collectability, engagement, conflicts. Every point is traceable to a line in the narrative. Your intake manager can argue with it, which is the only way anyone ever trusts a score.
A structured intake memorandum with the allegations, the liability picture, the medical posture, the coverage, the deadlines, the valuation range and the next three actions. The attorney opens a decision, not a transcript.
Practice area, current caseload, resolution rate, language, and your own tier rules. Cases outside your practice get a referral packet and a fee agreement instead of a polite no — the referral fee on cases you were never going to take is usually the first line item that pays for this.
Web forms, LSA, call transcripts, chat, referral email. Webhook or a polling connector into your CRM.
We tune weights and thresholds against 12–24 months of your own signed and declined cases.
It scores everything, changes nothing. Your team compares. You keep the disagreements.
SLA clocks, escalation, memos into Litify / Filevine / Clio Grow / Lawmatics. Then it runs.
One additional signed case a year covers the whole thing at every tier. Everything below is month-to-month after the initial term, and the setup fee is refundable if the shadow period does not beat your current intake on your own historical data.
| Inbound leads per month | 340 |
| Current signed-case rate | 8.5% → 28.9 cases/mo |
| Average fee per signed case | $29,000 |
| Year-one cost of Intake Triage AI ($9,500 + 12 × $3,400) | $50,300 |
| Break-even — additional signed cases needed in 12 months | 1.74 cases |
| Modeled uplift from faster contact + correct queue order (+0.9 pts) | 9.4% → 32.0 cases/mo |
| Incremental cases/yr, after a 40% haircut on the uplift | +22.0 |
| Incremental fee revenue, year one | $638,000 |
| Net year one · return · payback | $587,700 · 12.7× · 4.1 weeks |
Every input above is yours to change. At the teardown we replace all six assumptions with numbers pulled from your CRM, and if the model does not clear 4× on your own data we say so and you keep the analysis.
It does not. It ranks and summarizes; a human accepts or declines every single time. What changes is the order your team works the queue and how much context they have when they pick up the phone. In the two-week shadow period it scores everything and touches nothing — you get a side-by-side of its ranking against your paralegal's and you decide whether it earned any authority at all. Firms typically keep manual override on Tier A cases permanently. That is fine. The value is in the 60% of the queue nobody was reading carefully.
You are not replacing her. She is one person covering roughly 340 leads a month, which is 14 minutes of attention per lead if she does nothing else for eight hours a day, and she is asleep between 6pm and 8am when about 40% of accident-related form fills happen. This handles the first 60 seconds on all of them, at 2am, in Spanish, and hands her a ranked queue with memos already written. Most firms redeploy that person onto signed-case follow-up, which is where she was always more valuable.
It will. Every score shows its own arithmetic — which line in the narrative moved which factor and by how many points — so a wrong score is a visible, fixable disagreement rather than a silent one. Those disagreements are the calibration input; we retune weights monthly against what you actually signed. The deterministic rules engine also runs independently of any language model, so a model outage degrades the memo prose, never the score, the statute flag or the routing.
No. This runs on dedicated GPU hardware — three RTX PRO 6000s plus a local node cluster — with no third-party API in the path and no per-token metering. Narratives never leave infrastructure you can point at. For firms that need it, the whole stack deploys inside your own network and we hand over the runbook.
Two weeks to shadow mode, four weeks to live routing, and it sits beside your CRM rather than replacing anything. Integration is a webhook in and a memo plus a field write-back out. No data migration, no retraining your staff on a new system, no change to how a matter gets opened.
It ships with a per-practice-area, per-state limitations table plus the administrative deadlines that bite earlier — EEOC's 300 days, workers' comp employer notice windows. At setup we verify the table against your actual filing jurisdictions with your own counsel before it goes live. It is a flag that forces a human to look, not a legal opinion, and the memo says so on every page.
Discovery on your current intake flow, weight and threshold calibration against 12–24 months of your signed and declined history, the jurisdiction table build, CRM integration and field mapping, the two-week shadow evaluation with a written accuracy report, attorney roster and routing rules configuration, and staff training. It is refundable in full if the shadow report does not beat your current process on your own data.
Twenty minutes. Export whatever your CRM gives you, we run it through the engine on the call, and you see exactly which cases your queue ordered wrong and what that cost. You keep the analysis whether or not you buy anything.