This is general information, not legal advice, and reflects Ontario law and general AI-vendor practice as of September 16, 2026.
Why a PI file isn't a generic litigation file, for AI-vendor purposes
A generic legal-AI checklist tests for confidentiality and accuracy in the abstract. A personal injury file adds three things most checklists never ask about: whether the tool understands a medical-treatment timeline well enough to be useful, whether it treats an insurer's adjuster as a distinct correspondent worth tracking on its own, and whether a number it produces can be explained to a client and defended across the table from opposing counsel. None of that is exotic — it's specific, and vendor marketing pages tend to skip specifics.
The gap matters because PI firms are already leaning in. 56% of personal injury lawyers rate summarizing and analyzing medical records as a top AI priority, ahead of drafting correspondence (52%), brainstorming (46%), and drafting documents (39%) — per the same 8am 2025 report cited above. That speed, on files this sensitive, is where an unexamined vendor choice costs the most. As one 2026 field guide for plaintiff-side AI adoption puts it: "draft faster" isn't the metric — settling more, faster, with fewer errors is (Quilia, "AI for Personal Injury Law Firms: 2026 Field Guide"). The checklist below is built around that standard, not a feature list.
Group A — Case value, medical records, and demand drafting
Start with the work that actually drives a PI file's outcome, not the work that's easiest for a vendor to demo.
| # | Question | Why it matters | Red flag answer |
|---|---|---|---|
| 1 | Does the vendor disclose what feeds a case-value or settlement-forecast tool — historical verdicts, regional trends, your own firm's files — and give a confidence range instead of a bare number? | Predictive case-value tools score cases against historical verdicts, settlement data, and medical severity; the output is a data-backed starting point, not a replacement for a lawyer's judgment, and a tool that can't explain its inputs can't be defended to a client. | "Our AI predicts your settlement value," with no explanation of what feeds the model or how confident it is. |
| 2 | For AI-assisted medical-records review, does every extracted fact link back to a specific page in the source chart? | 2026 guidance for plaintiff-side AI tools recommends treating anything without page-level source citation, or below roughly 85–90% extraction accuracy, as unverified paralegal work — not a finished chronology (Quilia, 2026). | "Powered by AI" summaries with no citation trail back to the underlying record. |
| 3 | Does demand-letter drafting keep the lawyer in control of the amount, the tone, and how a pre-existing condition gets framed — or is it built to generate and send? | A demand letter is a negotiating document, not a template fill. The lawyer's framing judgment is the actual product; a workflow marketed as "press button, send" removes the control a plaintiff firm is paying to keep. | The tool markets a one-click send on a generated demand, with no required attorney edit step. |
Group B — Disbursements, insurer communication, and intake volume
This is the operational layer that determines whether a PI practice scales cleanly or drowns in its own file count.
| # | Question | Why it matters | Red flag answer |
|---|---|---|---|
| 4 | Can every reimbursable cost — records fees, expert reports, filing fees — be linked to the specific matter, with visibility into lien holders and settlement-distribution math? | Every dollar a firm spends chasing a file is a disbursement the client's recovery absorbs. A spend-tracking layer that isn't matter-linked forces someone to reconstruct the ledger by hand at settlement. | Cost tracking lives only in a general accounting module, with no per-matter linkage. |
| 5 | Does the tool track correspondence with an insurer or adjuster as a structured, searchable record — not just messages sitting in an inbox? | An insurer is a distinct kind of correspondent on a PI file: what was offered, what was disputed, and when a position changed all matter later, at mediation or trial. Treating insurer emails like any other message loses that history. | "We support email" is the entire answer to an insurer-tracking question. |
| 6 | Can intake absorb a PI firm's real inbound volume — most of which won't become a signed file — without losing or double-handling leads? | PI intake is a volume business before it's a caseload. Conservative auto-reject and aggressive auto-accept thresholds are what turn days of case-to-signature time into hours; a plain contact form isn't a triage layer. | Every inbound lead routes to the same human queue, with no triage logic at all. |
Group C — Data residency, privacy, and fitting the system you already run
| # | Question | Why it matters | Red flag answer |
|---|---|---|---|
| 7 | Where is the file physically stored, in writing — not "secure cloud infrastructure" on a sales call? | PI files carry some of the most sensitive personal data a law firm handles: medical charts, mental-health records, income history. A named region you can check against the vendor's own subprocessor list is the only real answer. | No named data-residency region anywhere in the vendor's documentation. |
| 8 | Is your firm's data used to train the vendor's underlying model, and can they state an exact retention window? | Ontario privacy guidance for lawyers is explicit that safeguarding client information extends to the third-party service providers a firm chooses — and not every cloud analytics platform stores or uses data the same way. | "We take security seriously," with no specific training-use or retention answer. |
| 9 | Does the tool integrate with — or at minimum migrate cleanly from — the case-management system you already run? | A scoring or drafting tool sitting outside your case data creates duplicate entry and stale output. Integration quality is a consistently cited failure point in 2026 evaluations of PI-specific AI tools. | Data only moves between systems through manual export and import, with no stated migration path. |
| 10 | Will the vendor say plainly what it does not do yet for personal injury specifically? | An honest gap disclosed before you sign costs nothing. The same gap discovered mid-file, during a real negotiation with an insurer, costs a settlement. | Every capability question gets some version of "yes, we handle that." |
What a real vendor answer should look like — for DROZlegal specifically: there is no case-value or settlement-forecasting tool today, full stop — that's a genuine gap, not a hedge. The platform's general document-intelligence core (Claude-powered summarization, due diligence, and contract-review tooling, used across every practice area) can process a medical record as a document, but there's no dedicated medical-chronology or causation-analysis tool built on top of it yet. A separate, narrower capability does exist: a records-request tracker that logs who holds a PI file's documents — insurers included, as one of several custodian types — along with each request's status and cost; we cover its exact shape in a dedicated post rather than repeat it here. Migration connectors exist for Clio, Cosmolex, and PCLaw — a one-time data migration in, not a live sync with a system you'd keep running alongside it. Contingency-fee billing has code behind it but isn't switched on in production today. What is live platform-wide: Canadian data residency (AWS ca-central-1, encrypted in transit and at rest) and AI processing under Anthropic's commercial API terms — inputs and outputs are never used to train models and are auto-deleted within roughly 30 days, which is not a zero-retention guarantee, since DROZlegal doesn't hold a separately negotiated zero-data-retention arrangement. That's the specific, gap-inclusive shape of an honest answer. A vendor that can't get this concrete about its own product isn't ready to answer it for yours.
Once you've worked through the checklist
Question 10 is the one worth returning to before you sign anything: our records-request tracking post is a case study in exactly that kind of disclosure, walking through what's live and what isn't for one narrow PI capability. If you also handle family files, our family law AI vendor checklist runs the same ten-question structure against a very different confidentiality problem. And if a shortlist is already forming, our free 32-item vendor due-diligence checklist scores a specific vendor across the categories this post only opens.
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