Constrained by our curated legal knowledge base. Every case name is cross-referenced, and anything unverified is flagged to you.
Digital documents are read locally in your browser. Scanned pages are the one exception: they have no text inside, so they are read by our AI under no-training terms to be turned into text. Personal identifiers are masked in the text before the analysis AI sees it. The AI does not train on your data. Encrypted at rest and in transit.
130+ UK credit hire precedents including Hussain, Lagden, Stevens, Dimond, and more. Every case includes a summary and key principles, with a link to the public judgment where one exists.
Custom AI prompts developed by credit hire professionals ensure responses are claimant-focused, well-structured, and practically useful.
Visual indicators show when responses are cross-referenced against our case law database. Limitations are clearly stated when authority cannot be confirmed.
Integrated Highway Code provisions, Road Traffic Act 1988, and Consumer Contracts Regulations 2013 for comprehensive legal reference.
Designed and maintained by people who work in credit hire every day - not generic AI developers.
Every AI output passes through three independent safety layers before it reaches you. Layers 2 and 3 currently report and flag rather than edit your text, so the final check stays with you.
1. Prompt Rules
The model is instructed to cite only from our closed knowledge base. Instructions guide the model but are not a technical guarantee, which is why layers 2 and 3 exist.
2. Citation Validator
Every case name the AI returns is cross-referenced against our verified database. Names that do not match never enter the citation list and are flagged to you in amber. The citation reference string itself is checked and reported, not enforced.
3. Text-Body Scrubber
A scanner catches any remaining "X v Y" patterns in the body text and flags the unverified ones for you to check. This is detection only while the matcher is in observe mode; automated removal is disabled because it was damaging correct citations.
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