# Intake Triage AI — Go-To-Market **Product:** Intake Triage AI **Operator:** Mike Rodgers (solo, RIG) **Buyer:** US plaintiff-side and small/mid-size law firms **Deal shape:** $4.5k–$18k setup + $1,450–$6,500/mo **Delivery:** self-hosted GPU fleet (3× RTX PRO 6000 + 4 LAN nodes, 293GB VRAM) — zero marginal inference cost --- ## 1. ICP Definition ### Primary ICP — "The bottlenecked contingency shop" | Dimension | Target | |---|---| | Firm size | 8–45 attorneys (sweet spot 12–25) | | Practice mix | ≥50% contingency: motor vehicle, premises, workers' comp, med-mal, product liability, mass tort | | Inbound lead volume | 180–900/month | | Paid acquisition | $25k–$120k/month across Google LSA, Google Search, Meta, TV/radio remnant | | Cost per lead | $95–$310 (LSA in PI runs $150–$300 in tier-1 metros) | | Intake staffing | 1–3 intake specialists, business hours only, plus a $1,200–$2,400/mo answering service | | CRM / case management | Litify, Filevine, SmartAdvocate, CasePeer, Clio Grow, Lawmatics, MyCase, Needles | | Geography | Any US metro with LSA competition; Texas, Florida, California, Georgia, Arizona, Nevada first | ### Who signs the check The **managing partner** or **owner attorney**. In firms >25 attorneys it is the **COO / Director of Operations**, and the managing partner still has veto. Nobody else can sign. Do not sell to a marketing director — they have a budget but no authority over intake process. ### Who blocks the deal 1. **The intake manager.** She hears "AI that scores leads" as "AI that replaces me." She must be in the first call and she must be positioned as the operator of the system, not the subject of it. If she is against it, the deal dies at implementation even after signature. 2. **The CRM vendor's CSM.** Will claim their platform "already does lead scoring." It usually does rules-based tagging, not narrative scoring, memo drafting or capacity-aware routing. Ask them to show a scored lead with a factor breakdown. They can't. 3. **Firm IT / outside MSP.** Fears anything touching client data. Answered by the self-hosted deployment. ### Disqualifiers — walk away - Fewer than 6 attorneys **and** under 80 leads/month. There is no bottleneck to remove; the payback story is fake. - Hourly-billing defense, insurance defense, or corporate firms. Lead scoring has no economic meaning without contingency. - Under $8k/month in paid acquisition. The leak is too small to fund the product. - No CRM at all (spreadsheets + Outlook). Integration cost exceeds the deal value; refer them to a CRM implementer first. - Firms in active malpractice litigation over an intake failure. They will want indemnity you cannot give. --- ## 2. Trigger Events Eight observable buying triggers. Each is checkable before you write the first line of an email. | # | Trigger | Where to detect it | What it means | |---|---|---|---| | 1 | Firm posts an **"Intake Specialist" / "Intake Coordinator" / "Legal Intake Representative"** req | LinkedIn Jobs, Indeed, ZipRecruiter; Apollo job-posting filter | They are trying to solve a queueing problem with headcount. This is the single highest-intent trigger. Email within 72 hours of the post. | | 2 | Firm is running **Google Local Services Ads** in a PI category | Search `[practice area] lawyer [city]` in an incognito window and look at the LSA carousel; check the Google Ads Transparency Center | They are paying $150–$300/lead. Every hour of intake lag is a measurable dollar. | | 3 | **Headcount growth of 15%+ in 12 months** with no ops hire | Apollo → organization employee growth; LinkedIn company page "employee growth" chart | Volume is outrunning process. Intake is already broken and they know it. | | 4 | **New partner or new practice-area announcement** | State bar journals, firm press page, Law.com regional, local business journal "People on the Move" | New matter types entering a queue that was tuned for the old mix. Routing rules are now wrong. | | 5 | **Mass-tort or MDL campaign launch** (Camp Lejeune, talc, Roundup, hair relaxer, AFFF successor) | AAJ litigation groups, firm blog, sudden Meta ad volume in the Meta Ad Library | Lead volume spikes 5–20× overnight. Manual intake collapses in week one. This is the most urgent buyer on the list. | | 6 | **New case-management system rollout** (Litify / Filevine / SmartAdvocate) | LinkedIn posts from firm staff, vendor case-study pages, G2 reviews with the firm named | Budget for legal tech is already approved and the change-management window is open. Ride the implementation. | | 7 | **Super Lawyers / Best Lawyers / rising-star listing** or a large verdict announcement | Super Lawyers directory, Justia, Avvo, firm press release, local news | Revenue event → marketing spend increase → lead volume increase → intake breaks 60–90 days later. Calendar the follow-up. | | 8 | **Managing partner posts about lead quality, marketing waste, or "we get 300 leads and sign 20"** | LinkedIn, LMA (Legal Marketing Association) discussions, PILMMA / Great Legal Marketing communities, r/LawFirm | They have already diagnosed the problem publicly. Quote their own post back to them. | --- ## 3. The First 10 Named Prospect Archetypes Deal size below is **year-one contract value** = setup + 12 months. ### 1. The LSA-Heavy Metro PI Firm 12–18 attorneys, one metro, $35k–$60k/mo on Google LSA + Search, ~340 leads/month, Filevine or SmartAdvocate. **Why they buy:** they can name their cost per lead to the dollar and cannot name their time-to-first-contact. **Deal:** ~$50,300 (Firm tier). **Find them:** Apollo — `industry: Law Practice`, `employees: 11–50`, `keywords: personal injury`, `location: [metro]`; cross-check the LSA carousel for `car accident lawyer [metro]`. Anyone in the top 3 LSA slots is spending real money. ### 2. The Mass-Tort Surge Shop 20–40 attorneys, currently running a single-tort campaign, 1,500–6,000 leads/month, CasePeer or Litify. **Why they buy:** the campaign already broke their intake and they are triaging with a Google Sheet. **Deal:** ~$96,000 (Multi-office tier). **Find them:** Meta Ad Library — search the tort name, filter to advertisers with 50+ active creatives; then AAJ litigation group rosters for the same tort. ### 3. The Two-Office Regional Injury Firm 25–45 attorneys, 2–4 offices across state lines, ~700 leads/month, different SLAs per office. **Why they buy:** cross-office routing is manual and the SOL table differs by state. **Deal:** ~$96,000. **Find them:** LinkedIn Sales Navigator — `Law Practice`, `51–200 employees`, `title: Managing Partner OR Chief Operating Officer`, `geography: [state]`; filter to firms with multiple listed office locations on their site footer. ### 4. The Workers' Comp Volume Shop 10–20 attorneys, 800+ leads/month at low value per case, thin margins. **Why they buy:** margin per case is small, so wasted attorney minutes matter more here than anywhere. **Deal:** ~$50,300. **Find them:** Apollo — `keywords: workers compensation`, `employees: 11–50`; plus state workers' comp bar section rosters. ### 5. The Med-Mal Boutique 6–14 attorneys, only 60–150 leads/month but each case is worth $150k–$900k in fees, extremely high decline rate. **Why they buy:** they decline 90%+ of inbound, and each unqualified consult costs a physician-expert screening hour. **Deal:** ~$21,900 (Desk tier) — small ticket, exceptional reference logo. **Find them:** AAJ Medical Negligence litigation group; Super Lawyers `Medical Malpractice – Plaintiff` listings by metro. ### 6. The Employment Plaintiff Firm 8–20 attorneys, wrongful termination + wage & hour, 200–400 leads/month, hard EEOC 300-day clock on every file. **Why they buy:** the administrative deadline, not the SOL, is what kills their cases. The flag alone sells it. **Deal:** ~$50,300. **Find them:** NELA (National Employment Lawyers Association) chapter member directories; Apollo `keywords: employment law, wrongful termination`. ### 7. The Spanish-Market Injury Firm 10–25 attorneys, 40–70% Spanish-language intake, heavy TV/radio, Houston / LA / Miami / Phoenix / San Antonio. **Why they buy:** bilingual intake staff are the scarcest resource in the building; nights and weekends are unstaffed. **Deal:** ~$50,300. **Find them:** LSA carousel for `abogado de accidentes [ciudad]`; Meta Ad Library filtered to Spanish-language creative. ### 8. The Post-Verdict Growth Firm Just announced a 7- or 8-figure verdict, hiring 3+ attorneys, marketing budget just doubled. **Why they buy:** volume is about to arrive and they know last year's process will not hold. **Deal:** ~$50,300–$96,000. **Find them:** Law.com regional verdict roundups, local business journal, the firm's own press page, LinkedIn hiring signal. ### 9. The Filevine/Litify Implementation Firm Any size, mid-rollout of a new case management system. **Why they buy:** budget approved, integration appetite at its annual maximum, and the CRM does not solve intake triage. **Deal:** ~$50,300. **Find them:** vendor customer/case-study pages, G2 and Capterra reviews with firm names, LinkedIn posts containing "excited to announce we're moving to Filevine." ### 10. The Solo/Small Firm With an Outsized Ad Budget 4–8 attorneys, $20k–$40k/mo on ads, no dedicated intake person — the paralegal does it between filings. **Why they buy:** they are the most obviously broken and the fastest close, but the smallest ticket. **Deal:** ~$21,900 (Desk tier). **Find them:** LSA carousel positions 4–8 in secondary metros; Avvo/Justia profiles with heavy paid placement. --- ## 4. The 5-Email Cold Sequence **Sending rules:** one thread, plain text, no images, no tracking pixel, no unsubscribe footer on a cold B2B thread under 300 sends/day. Send from a warmed domain. Personalize line one of every email or do not send it. --- ### Email 1 — Day 0 **Subject:** your LSA spot for "car accident lawyer {{city}}" > {{FirstName}} — you're in the top three LSA slots for car accident lawyer {{city}}, so you're paying somewhere north > of $180 a lead. > > The question I'd ask is what happens to that lead at 9:40pm on a Saturday. > > At most firms your size it sits until Monday, and by Monday two other firms with an answering service have already > called. The lead was never bad. The queue was. > > I build a system that scores every inbound lead the second it lands, flags the statute, writes the intake memo and > puts it on the right attorney's desk. Runs at 2am. > > Worth 20 minutes to look at your last 30 days of intake together? > > — Mike --- ### Email 2 — Day 3 **Subject:** the 40% of your leads that arrive after hours > Quick number: roughly 40% of accident-related form fills happen between 6pm and 8am. If intake is business-hours, > that's 4 of every 10 leads you paid for getting a same-day-next-morning callback at best. > > {{FirstName}}, at {{leadsPerMonth}} leads a month and {{cpl}} a lead, that's about {{afterHoursSpend}} a month > landing in a queue nobody is watching. > > I'm not selling you an answering service. I'm saying the first sixty seconds — score it, flag the statute, write the > memo, route it — should not require a human to be awake. > > 20 minutes? > > — Mike --- ### Email 3 — Day 7 **Subject:** the one that has 14 days left on the statute > {{FirstName}} — here's the failure mode that actually costs money, and it isn't the slow callback. > > A lead comes in describing an incident from 22 months ago. In a two-year state that's 60 days of runway. It goes into > the same queue as the fender bender from Tuesday, in arrival order, and nobody sees the clock until someone opens it. > > Every score my system produces carries a days-remaining number on the statute, plus the administrative deadlines that > bite earlier — EEOC's 300 days, comp notice windows. Anything under 120 days jumps the queue and pages a partner. > > One of those a year is worth more than the whole system costs. > > Want me to run your last month's intake export through it? You keep the output either way. > > — Mike --- ### Email 4 — Day 12 **Subject:** built this on my own hardware, here's what it looks like > {{FirstName}} — rather than describe it again, here's the live thing: {{demoUrl}} > > Thirty sample intakes. Click any one and you'll see the score, and under it, every factor that produced the score and > the exact line in the caller's narrative that moved it. There's no black box to argue with — which is the only reason > an intake manager ever trusts one of these. > > It runs on my own GPUs. No OpenAI, no per-token bill, and for firms that want it, it deploys inside your network. > > If it's useful, the next step is 20 minutes with your actual numbers. > > — Mike --- ### Email 5 — Day 20 (breakup) **Subject:** closing your file > {{FirstName}} — I'll stop here. > > Best guess from the outside: {{leadsPerMonth}} leads a month, one or two people reading them in the order they > arrived, and somewhere between four and eight signable cases a year going to whoever called first. I could be wrong > about all of it — you'd know. > > If intake ever becomes the thing you're annoyed about, my inbox stays open and the demo stays up at {{demoUrl}}. > > Good luck with the {{recentThing}}. > > — Mike --- ## 5. Three LinkedIn Posts --- ### Post 1 — the number > I pulled the intake log from a 14-attorney injury firm last month. > > 312 inbound leads. Median time from web form to first human callback: 11 hours 24 minutes. > > Then I sorted the same 312 leads by how good they actually were — commercial defendant, police report, ER visit, > named carrier, statute runway. > > The single best case in the file waited 19 hours. > > It wasn't sitting there because anyone was lazy. It was sitting there because it arrived at 8:40 on a Friday night > and the queue is a queue. First in, first read. That ordering is the entire problem, and no amount of hustle fixes > ordering. > > They pay about $190 a lead. So that $190 bought a case worth roughly $70,000 in fees, and then the process handed it > to whichever firm had someone awake. > > Intake isn't a staffing problem. It's a sorting problem. Sorting is the one thing a machine is unambiguously better > at than a tired human at 8:40 on a Friday. --- ### Post 2 — the contrarian take > Unpopular opinion: your intake person is not the bottleneck. Your intake *queue* is, and hiring a second intake > person makes it worse. > > Here's the math nobody runs. 340 leads a month, one specialist, eight-hour day. That's 14 minutes per lead if she > does literally nothing else — no callbacks, no follow-ups, no retainer chasing, no bathroom. She does all of those > things, so real attention per lead is maybe four minutes. > > Add a second person and you get eight minutes per lead and a new coordination problem about who owns which lead. > You've doubled cost to buy four minutes. > > The actual fix is to stop making a human do the part humans are worst at: reading 340 narratives in arrival order and > holding a consistent quality bar across all of them at 4:55pm on a Friday. > > Score first. Sort second. Then put your best human on the top of a correctly-sorted stack, where she's worth what you > pay her. > > Same headcount. Different order. --- ### Post 3 — build in public > Spent the weekend building an intake triage system for law firms. Here's what's actually under it. > > Seven weighted factors: practice-area fit, liability language pulled straight out of the caller's own words, damages > severity from treatment posture, statute runway by state and practice area, collectability from the named carrier, > claimant engagement, and conflicts. > > The part I care about: every single point is traceable. If a lead scores 84, you can see that "rear-ended" added 9, > "the driver apologized" added 8, and "I might have been looking at my phone" took 10 back off. Your intake manager > can argue with it line by line. > > That matters more than the accuracy. Nobody adopts a score they can't argue with. > > The whole thing runs on three RTX PRO 6000s in my office plus four LAN nodes. 293GB of VRAM, no OpenAI in the path, > no per-token bill, and no client narrative leaving hardware I can point at. > > Live demo is up. 30 sample intakes, all synthetic. Click one and it shows you its work. --- ## 6. Top 3 Objections + Answers ### Objection 1 — "I'm not letting software decide which cases we take." It doesn't decide. It ranks and it summarizes; a human accepts or declines every single file, 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. The first two weeks are shadow mode — it scores everything and touches nothing. At the end you get a side-by-side of its ranking against your intake manager's on the same 300 leads, and you decide whether it earned any authority at all. Most firms keep manual override on Tier A permanently. That's fine. The value was never in the top 10% of your queue that everyone already reads carefully. It's in the 60% nobody does. ### Objection 2 — "Our CRM already has lead scoring." Show me a scored lead in it. What you'll see is rules-based tagging: source, practice area, maybe a checkbox for police report. What you won't see is anything that read the narrative. The difference is concrete. "Rear-ended by a delivery truck, driver apologized, cited at the scene, ER visit, State Farm policy" and "minor fender bender, no police, I might have been on my phone, no treatment yet" are the same record in Litify — same source, same practice area, same state. They are 40 points apart here, and one of them is worth $70,000. Your CRM also isn't writing the memo or checking whether the statute ran. ### Objection 3 — "What does this cost me if it's wrong?" Less than what being right slowly costs you today, and here's why the downside is bounded. The scoring engine is deterministic rules, not a language model — a model outage degrades the prose quality of the memo and nothing else. The score, the statute flag, the conflict check and the routing all keep working. Nothing is ever auto-declined; low scores get a slower SLA, not a closed file. And every score shows its own arithmetic, so a wrong score is a visible disagreement you can correct, not a silent one you find out about in a malpractice deposition. The real number: $50,300 in year one at the Firm tier. Break-even is 1.74 additional signed cases at a $29,000 average fee. If it produces fewer than two extra cases in twelve months, it failed and you should fire me. --- ## 7. Channel Plan — first 90 days | Weeks | Motion | Target | Success metric | |---|---|---|---| | 1–2 | Build the list. Apollo (`Law Practice`, 11–50 employees, PI/employment/med-mal keywords, 40 metros) + LSA carousel scrape + LinkedIn "Intake Specialist" job-post monitor. | 600 firms, 900 contacts | ≥85% deliverable, managing-partner-level contacts | | 3–6 | Cold email sequence, 40/day from one warmed domain. Trigger-tiered: job-post firms first. | 480 sends | 3–5% reply, 8–12 booked teardowns | | 3–12 | LinkedIn: 3 posts/week from the bank above, plus a comment pass on PILMMA / LMA / legal-marketing threads. | — | 2–4 inbound teardowns | | 5–12 | Teardown → 2-week paid pilot ($2,500, credited to setup) → contract. | 20 teardowns | 5 pilots, 3 closes | | 9–13 | Case study from pilot #1. That artifact replaces cold volume in month 4. | 1 written case study | first referral | **Ninety-day target: 3 signed at Firm tier = $28,500 setup + $10,200/mo recurring.** --- ## 8. Gate-D note Nothing in this document has been sent. The email sequence, the LinkedIn posts and the prospect list are drafts staged for approval. Apollo enrichment and any outbound send require typed operator approval before execution.