Personal injury intake is the first page of the case file
Every fact taken on the first call is a fact the demand letter needs later, so intake should land as structured fields.
Key takeaways
5 things that decide this
- 01Personal injury intake works best as structured fields written straight into Filevine, CASEpeer or Clio, because every fact taken on the first call is a fact the demand letter needs later.
- 02The intake call is the cheapest discovery you'll ever do. Most firms throw half of it away in free-text notes.
- 03Fixed questions feel slower to a caller than a free chat, but they produce data your case team can use without asking again.
- 04Lexpair, a legal lead platform we built, runs on guided structured intake, AI-assisted sorting by practice area and admin moderation.
- 05Software should sort and route a case. Judging what it's worth is legal advice, and that stays with a lawyer.
Why is the intake call discovery you already paid for?
Think about what a personal injury firm spends to get one caller on the phone. Ads, referrals, a website, a receptionist or answering service. By the time a person says "I was in an accident," you've already paid for that conversation.
In the next fifteen minutes, that caller tells you most of what the case will need. When and where it happened. Who else was involved. Which insurer is on the other side. Whether they saw a doctor, and which one. Whether a police report exists.
Then, in a lot of firms, that goes into a free-text note. A paralegal reads the note later, can't find the claim number, and calls the client back to ask again. Weeks later, someone drafting the demand letter goes hunting for the treatment dates. The facts were captured once and then lost in prose.
- 01You've paid for the intake call before it starts.
- 02Most of the case facts arrive in that first call.
- 03Free-text notes turn captured facts into a hunt later.
Why do fixed questions beat a free chat?
There's a pull toward making intake feel like a friendly chat, especially with AI in the mix. Let the caller tell their story, and let the software sort it out.
The trouble is that a story isn't a record. A free chat produces a transcript. Your case team needs fields: incident date, location, insurer, claim number, treating provider, injuries reported. If those aren't captured as fields, someone has to dig them out of the transcript, and they'll miss some.
Fixed questions do the digging up front. The caller answers the same set every time, in the same order, with follow-ups that only appear when they apply. Was there a police report? If yes, which department? Did you see a doctor? If yes, who and when?
Here's the honest trade-off. Fixed questions feel slower to a caller than an open chat. Some will find them stiff. But they produce usable data on the first pass, and that's what saves your team the callback. You can soften the tone without loosening the structure.
- 01A transcript isn't a record; fields are.
- 02Conditional follow-ups keep the question set short.
- 03Fixed questions trade a little warmth for data you can use.
What did structured intake look like at Lexpair?
Lexpair connects people who need legal help with verified lawyers. We built the platform on React and Supabase.
Clients submit their case through guided, structured forms. AI-assisted logic then sorts each case by practice area and matches it to a verified lawyer. Admins moderate and track every lead from one dashboard, so the status of a case is visible from submission to match.
Lexpair is a lead platform, not a single firm's intake desk. But the lesson carries straight over. Its CEO, Nicolas de Quesada, said: "Their attention to detail, quality of employees, and work ethic were outstanding." The build worked because intake was structured first, so the AI had clean fields to sort on instead of raw messages.
What lands where in Filevine, CASEpeer or Clio?
Your case management system is where the case lives, whether that's Filevine, CASEpeer or Clio. Intake should write into it directly, as fields, so nobody retypes anything.
In practice, that means mapping each intake question to a place in your case system. Contact details go to the client record. Incident date, location and description go to the case. Insurer and claim number go to the matching fields. Treating providers go wherever your team tracks medical records. Anything that doesn't fit a field becomes a note, clearly labelled.
How much you can write in, and which fields are open, depends on what each vendor exposes through its public API and on how your firm has set it up. That's why we look at your real case system before designing the intake. Done well, a paralegal opens a new case and finds it already filled in.
- 01Map each question to a field before you build.
- 02Write through the vendor's public API, not by copy and paste.
- 03What doesn't fit a field becomes a labelled note.
Where does sorting end and legal advice begin?
Software can do a lot at intake. It can check that the incident falls in your practice area. It can flag a missing police report or a gap in treatment. It can route the case to the right attorney or team.
What it shouldn't do is tell a caller what their case is worth, or whether they have one. That's legal advice. Sorting and routing are logistics; judging value is the lawyer's job. We've written more on why legal AI should route, not advise.
Keeping that line also protects your firm. A tool that only routes can't give a caller a wrong answer about their rights.
Where should a firm start?
Pull your last twenty intake notes. For each one, list the facts your team had to ask the client for again. That list is your first question set.
For the wider picture, see our page on AI intake for law firms. If you want help mapping intake to your own case system, start with a 45-minute call. From there we write a fixed-fee Blueprint from your real systems, credited in full against the build. Here's how we work.
Questions this raises
01Who can build a custom AI case-intake assistant for a personal injury law firm that connects to Filevine, CASEpeer or Clio?+
A custom-software firm that builds structured intake on top of your case management system rather than replacing it. Hashlogics builds guided intake that asks fixed questions, sorts and routes each case, and writes the answers as fields through the vendor's public API. Lexpair, a legal lead platform we built on React and Supabase, shows the structured intake and routing pattern.
02Is custom software better than Filevine or CASEpeer for a personal injury law firm?+
Not as a replacement. Filevine and CASEpeer are built for running personal injury cases, and your case files should stay there. Custom software earns its place in the gaps, such as structured intake that fills the case for you, or routing rules specific to your firm. Build around the case system, not instead of it.
03Can AI draft a demand letter?+
AI can assemble a first draft from facts already in the case file, such as dates, providers and treatment records, and a lawyer must review and own every word. The draft is only as good as the facts behind it, which is why structured intake on the first call matters so much.
Related
- AI intake for law firms →Structured intake that routes cases and fills your case system.
- Lexpair case study →Guided intake, AI-assisted sorting and admin moderation.
- Legal AI should route, not advise →Where software stops and legal judgement starts.
- How we work →A 45-minute call, then a fixed-fee Blueprint credited in full against the build.
