Practical guides to witness statements, credit hire disputes, and legal document strategy.
Thomson Reuters has launched its own frontier model. The interesting part is not that they did it. It is that they began with an open-source foundation, spent about 450,000 dollars on the training run, and still run other models alongside it. That is the whole argument about legal AI, settled by the company with the most to gain from the opposite answer.
The claimant's statement is usually the only factual evidence on need, period and impecuniosity, and once served it stands as evidence in chief. This is the section-by-section build: what Practice Direction 32 actually requires, what is convention rather than rule, and what Wiltshire v Aioi really criticised about template statements.
Part 32 and Practice Direction 32 set out what a witness statement must contain, how it must be verified, and what the court can do when it falls short. This is the working reference: the mandatory content of paragraph 18.1, the statement of truth wording, what CPR 32.14 does about a false one, and the five compliance failures that show up most in credit hire files.
One claimant firm reports a 230 percent year-on-year rise in ADR cases. In arbitration and mediation there is no cross-examination and no judge to persuade in person. The paper does all the work.
Ziyaad Ahmed of Qanooni AI argued in Legal Futures this week that legal AI has three layers: model, product, firm. Only the firm layer, he says, holds durable value. He is right about the model layer and the product layer. Here is what his three-layer model does not quite capture, and why it matters for claimant firms picking specialist tools.
The Civil Justice Council is consulting on new rules for AI in trial witness statements. The debate has largely missed an existing rule already sitting in the Civil Procedure Rules. Practice Direction 32 paragraph 18.1(5) requires every witness statement to disclose the process by which it was prepared. Here is what that already covers, what CRM automation is already caught by it, and where a blanket ban on AI would reach further than the drafters probably intend.
Motor injury and OIC volumes fell again in 2025 to the lowest on record. For claimant law firms, fewer and harder cases change the economics of every file.
The Upper Tribunal has now said it explicitly. Pasting client information into ChatGPT places that information in the public domain, breaches confidentiality, and waives legal privilege. What the ruling means and what firms should be doing this week.
A senior High Court judge said a junior solicitor 'almost entirely outsourced the thinking process' to AI. What the ruling means for claimant law and credit hire operations, and the three failure modes to design against.
Real examples of AI hallucination in legal contexts, the difference between general AI and verified knowledge bases, and what to look for in a legal AI tool.
The court's criticism of template-driven witness statements, what credit hire teams should change, and how guided drafting reduces compliance risk.
Understanding what Bunting v Zurich actually decided about BHR evidence and why rigorous factual challenges at first instance remain essential.
What does impecuniosity mean in UK credit hire? A practical guide to pleading, proving, and defending it, grounded in Lagden v O'Connor and recent case law.
Credit hire teams spend hours manually researching and responding to TPI insurer correspondence. Here's what that costs, and what the alternative looks like.
How the OIC portal and whiplash reforms affect credit hire operations, fraud patterns, and claim strategy in 2026.
In legal claims work, language models need a curated knowledge base to be trustworthy. Here's why architecture matters for credit hire AI.
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