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Home › Reports › PI AI vendor watch: Q4 2026

PI AI vendor watch

New tools and pricing, Q4 2026

39 vendors name personal injury firms on their own pages. 17 say their output cites the source page. 15 publish a price.

By Ahmed Jemaa, Co-Founder & CEO of Medrecords AI · Published 7 Sep 2026 · Updated 14 Sep 2026 · Sources checked 13 Aug 2026 to 7 Sep 2026Summarize with ChatGPT, Claude, Perplexity or Google AI

What happened, with dates

DateVendorEventLink
2025-12Bevaya (Roots Automation)Claims 93 percent loss-run accuracy on a self-run December 2025 benchmarksource
2025-12-31RiskAngleRiskAngle acquired by Hiren Patel and Rewisoftsource
2026-02-12HealthMark GroupHealthMark acquired Purview, expanding into digital medical imaging deliverysource
2026-02-25ExlService Holdings (EXLS)Introduced the exldata.ai agentic data solutions suite in Q4, with named client wins in fintech and healthcaresource
2026-04-29Verisk Analytics (VRSK)Described momentum in commercializing multi-year investments in agentic technologiessource
2026-04-30CCC Intelligent Solutions (CCC)Said AI solutions are the fastest-growing part of the portfoliosource
2026-06-04Guidewire Software (GWRE)Described agentic capabilities embedded in the claims adjuster workflowsource
2026-07-21Marsh & McLennan (MMC)Introduced Atlas, an AI-enabled platform, and Lenwork, an agentic assistantsource
2026-07-29ExlService Holdings (EXLS)Went live at a large national health plan with its first customer-facing agentic AI modulesource
2026-07-29Verisk Analytics (VRSK)Closed the acquisition of McKenzie Intelligence Services and moved property and casualty data sets into AI-ready environmentssource
2026-07-30CCC Intelligent Solutions (CCC)Said carriers are moving AI from pilots to full deployments in casualty and subrogationsource

How many vendors are behind the numbers on this page?

39. A vendor is counted for personal injury firms only when it names that audience on its own commercial pages and carries page-level evidence in this study. The full pool is 364 companies, of which 90 carry that evidence.

At a glance
39Vendors counted
200Sources linked
1094Pages captured
172Reviews coded
On this page
  1. At a glance
  2. The article
  3. Methodology
  4. Sources
  5. Frequently asked
  6. More in this series
  7. How Medrecords AI does this work
  8. Explore the content hub
  9. See it on a file

The article

What changed in the last quarter for AI tools sold to the PI attorney: new vendors, launches, pricing, language?

What the data says
  • 39 vendors name personal injury firms on their own commercial pages. 17 of them say the output cites back to the source page.
  • 15 of 39 publish a price a buyer can act on without a sales call.
  • Of 74 public reviews of AI vendors in this category, 2 mention accuracy or error at all.
17
dated events since January 2025
funding, acquisitions, launches
10 of 39
publish an llms.txt file
pulled 2026-09-06 to 2026-09-07
12 of 39
publish sitemap dates we can measure
the rest are recorded as not measured
1
block AI crawlers in robots.txt
in this audience set

The language moved before the products did

The clearest signal of where this category is going is what its own homepages say. We pulled archived snapshots near 1 September in 2024, 2025 and 2026 and counted the same terms in each.

TermSept 2024Sept 2025Sept 2026Change
agentic015+5
citation or cited3210+7
verify or verification7711+4
chronology152020+5
human, nurse or physician review111no change
hallucination001+1

Out of 35 vendors with a snapshot near 1 September in all 3 years: American Retrieval Company, CLARA Analytics, MedChrons, everchron.com, EvolutionIQ, Flatworld Solutions, Hathr AI, Hona, Enlyte, owl.co, paxton.ai, rate-fast.com, yocierge.com, plus 22 vendors not named here.

How the category's own homepages changed their language

sites using each term at least once, out of 35 with archived snapshots in all 3 years

■ Sept 2024 ■ Sept 2025 ■ Sept 2026agentic015citation or cited3210verify or verification7711chronology152020human, nurse or physician review111hallucination001

Directional only. Homepages alone, and only the vendors the Internet Archive happened to capture near 1 September in each of the 3 years. Every snapshot is linked in sources.

Agentic went from 0 sites to 5 in 2 years. Citation language moved from 3 to 10, which is the fastest climb on the chart. Chronology was already the settled word and stayed there at 20 of 35.

Hallucination appears on 1 homepage in 2026 and 0 in 2024. Marketing departments will name the capability long before they name the failure mode, which is exactly why the buyer has to test for it rather than read for it.

Who is shipping

A public sitemap with lastmod dates is a free view into whether a company is still building. This measures the site, not the product, and a marketing site can move while an engineering team does not. Treat it as one signal among several.

Which sites are actually shipping

share of dated sitemap URLs changed in the last 180 days

the vendor100%the vendor100%owl.co100%rootsautomation.com99%Hona92%Hathr AI90%the vendor86%the vendor80%MedChrons74%the vendor74%the vendor71%the vendor63%

Measured from public sitemaps on 2026-09-06 to 2026-09-07. 9 vendors in this set publish no lastmod dates, so their velocity is recorded as not measured rather than as zero.

Openness

10 of 39 vendors in this set publish an llms.txt file, the plain-text file that tells an AI agent what a site contains. Newer entrants publish it far more often than the incumbents, which is a fair proxy for who expects to be found by an agent rather than by a salesperson.

1 vendors in this set block AI crawlers outright: the vendor.

What to watch next quarter

  • Whether published prices spread. A single competitor printing a number tends to force the others.
  • Whether citation language moves from blog posts onto product pages.
  • Whether the roll-ups keep buying, and what happens to the acquired products' pricing after they are absorbed.
  • Whether anyone starts naming hallucination on a product page instead of only in a security whitepaper.

Methodology

This is a secondary-research study, not a survey. Every number is a count over a named set of vendors, taken from what those vendors publish on their own sites, with a source URL and a capture date.

This article
39vendors counted
5677coded evidence rows
1094pages captured
172reviews coded

What we did

  1. We built a vendor pool from 2 owned corpora: a 55-site competitor scrape captured on 2026-08-13, and 328 live company profiles from the Medrecords AI content hub.
  2. We ran 4 targeted discovery passes for the audiences the pool covered thinly: legal nurse consultants, medical expert witnesses, life care planners, and California QMEs. Those passes added 36 vendors that name those buyers on their own commercial pages.
  3. We coded a fixed rubric against every page we hold. A rubric field is marked yes only when the vendor's own copy says it, and each yes carries the page URL, the capture date, and a verbatim excerpt of 15 words or fewer.
  4. We pulled each vendor's sitemap, llms.txt, and robots.txt live on 2026-09-06 and 2026-09-07 to measure how often the site changes and whether it invites or blocks AI crawlers.
  5. We pulled Wayback Machine snapshots near 1 September of 2024, 2025, and 2026 and counted 7 marketing terms in each, to show how the category's own language moved.
  6. We read 174 third-party reviews and 30 Reddit threads and coded them into themes. Only hand-verified quotes are published.
  7. We scored each vendor for each audience on 6 weighted components and published the component scores next to the total, so a reader can disagree with a weight and re-rank.

How a claim is scored

Each rubric field is scored from the vendor's own pages, never from a press release or a third-party listing. Strength records where the claim appears, because a claim on a pricing page is worth more than a claim in a blog post.

StrengthWhat it means
strongStated at least twice on a key page, or at least 4 times across the site. Key pages are the homepage, product, pricing, security, solutions, platform, features, integrations, trust, compliance, and about pages.
mediumStated once on a key page, or at least twice elsewhere.
weakOne passing mention anywhere on the site.

Capture dates

WhatWhen
Competitor site scrape2026-08-13
Content hub profiles2026-09-01
Reviews and reddit2026-08-13
Discovery passes2026-09-06
Sitemap llms robots pull2026-09-06 to 2026-09-07
Wayback targets2024-09-01, 2025-09-01, 2026-09-01
Rankings computed2026-09-07

Limitations

  • This measures what vendors publish, not what their software does. A vendor that cites to the source page but never says so scores low here. That is the method working as intended: the study is about the public record, and a buyer reading a website sees the same thing.
  • Coverage is uneven by design. 55 vendors have a deep page-level scrape. 35 more were found by targeted discovery and scraped shallowly. The rest appear in the pool for completeness and are never ranked.
  • Update velocity can only be measured where a sitemap publishes lastmod dates. 60 vendors do. For the others the field is recorded as not measured, never as zero.
  • Wayback coverage is thin. The Internet Archive holds snapshots near all 3 target dates for 35 of the 55 deep-corpus vendors. Term trends drawn from that subset are directional and are labeled as such wherever they appear.
  • Review counts favor vendors that sell to law firms, because those are the vendors with public review profiles. A physician-facing product with no G2 listing is not worse, it is unlisted.
  • Prices are list prices published on a pricing page. Negotiated and enterprise pricing is invisible to this method, and most enterprise vendors publish no price at all.
  • Every count is a count over this vendor set on these dates. It is not a market share estimate and it is not a projection.

Gates we skipped and tools we could not use

  • openseo organic metrics. Dataset-build step 13 is optional and costs credits. It was not run, because a batch over 2,000 credits needs founder approval and none was given. No organic-traffic or keyword figure appears anywhere in this study.
  • Full 6-page scrape of discovery vendors. Dataset-build step 7 was completed for the 55 deep-corpus vendors and only partly for the 35 discovery vendors. Those vendors carry audience, pricing, and citation evidence from the pages actually fetched, and are marked discovery_pass so a reader can see the difference.
  • LibreOffice recalculation. The source checklist is an xlsx workbook. LibreOffice is not installed on the build machine, so the workbook was read with openpyxl and never recalculated. No figure in this study comes from a workbook formula.
  • Reddit direct access. Reddit blocks direct fetching from this machine. The 30 threads were captured through a third-party scraping API on 2026-08-13 and are quoted only where hand-verified.
  • Regulatory text verification. Statutory and regulatory citations marked verify in the source checklist have not been checked against current text. None of them is used as a number in this study.
  • Wayback CDX queries rate-limit hard under parallel load. The first pass lost 28 vendors to connection refusals. Those were retried serially with four-second spacing, which recovered most of them. The count above (122 snapshots) is what actually returned, not what was requested.
  • Exactly 5 vendor in the pool blocks AI crawlers in robots.txt: mosmedicalrecordreview.com, ecsper.com, provalens.ai, doqtor.io, smartmd.com.

Composites

Where this study describes a buyer situation rather than a vendor claim, it is a composite drawn from published sources, not a survey. Composites are labeled at the point of use with the number of sources behind them. No customer, prospect, or call participant is identified.

Review quotes are one excerpt per review, under 15 words, in straight quotes, linked to the review. Everything else is paraphrased and aggregated into coded themes.

Every table and chart in this series links to the page it came from. Where a page has changed since capture, the capture date printed next to the figure is the date that matters. Wayback links are given for figures drawn from archived snapshots.

Sources

200 sources. Every figure in this article traces to one of them. External links are marked nofollow and open in a new tab. Earnings call transcripts sit in our own corpus and carry no public link, so they are listed by company and quarter for anyone who wants to pull the original.

Vendor pages that name personal injury firms (39)

Pricing pages (11)

Funding, acquisition and product announcements (16)

Prices as of 7 Sep 2026.

Earnings call transcripts in the owned corpus (8)

  • ExlService Holdings (EXLS), Q4 2025 earnings call · 2026-02-25
  • Verisk Analytics (VRSK), Q1 2026 earnings call · 2026-04-29
  • CCC Intelligent Solutions (CCC), Q1 2026 earnings call · 2026-04-30
  • Guidewire Software (GWRE), Q3 FY2026 earnings call · 2026-06-04
  • Marsh & McLennan (MMC), Q2 2026 earnings call · 2026-07-21
  • ExlService Holdings (EXLS), Q2 2026 earnings call · 2026-07-29
  • Verisk Analytics (VRSK), Q2 2026 earnings call · 2026-07-29
  • CCC Intelligent Solutions (CCC), Q2 2026 earnings call · 2026-07-30

Court decisions (5)

Internet Archive snapshots (105)

Reviews and threads quoted (16)

Watch it in the app

3 short guides from our help center, recorded on a demo case. They play inside the app: sign in or create a free account, and the video opens at the chapter you picked. First case is free on us.

Frequently asked

Is this a survey?

No. Nobody was interviewed and nobody filled in a form. Every number is a count over a named set of vendors, taken from what those vendors publish on their own sites, with a source link and a capture date next to it.

How many vendors are behind the numbers on this page?

39. A vendor is counted for personal injury firms only when it names that audience on its own commercial pages and carries page-level evidence in this study. The full pool is 364 companies, of which 90 carry that evidence.

What does it mean when a vendor is not counted for a capability?

It means the claim does not appear on any page we captured. It does not mean the software cannot do it. This study measures the public record, which is also what a buyer reading a website sees.

Why do the reviews say so little about accuracy?

Of 74 public reviews of AI and software vendors in this category, 2 mention accuracy or error and 0 mention hallucination. Reviewers write about what they can see. Turnaround is visible immediately. A missed record is not visible until it matters.

Can I check your work?

Yes, and that is the point. Every table links to the page it came from and prints the date we read it. Where a figure comes from an archived snapshot, the snapshot link is in the sources section.

Does Medrecords AI appear in the ranking?

No. We publish this study, so ranking ourselves against our own rubric would not be a ranking. The rubric and every input are public, so anyone can score us on the same sheet.

How Medrecords AI does this work

Medical chronology

A dated, deduplicated timeline with a citation on every entry.

Product

Medical record Q&A

Question the whole record in plain English; every answer cited.

Product

Verifiable AI citations

If it is not cited, it is not said.

Product

Explore the content hub

State programs

Rules, AMA Guides edition, and MMI standards by state.

Guides

Editorial reference on report writing, MMI, and validity testing.

Conferences & events

Workers comp, claims, insurance and medical-legal conferences.

Directories

Rosters of examiners, LNCs, and expert witnesses by state.

State matrix report

All 10 verified state programs, side by side.
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