Microsoft invested billions in AI capabilities. Copilot performs genuinely impressive tasks — document summarisation, email drafting, meeting notes. But legal work is not about creating content. It is about being right. And that is where general-purpose AI breaks down in legal practice.
The hallucination problem is structural
Copilot presents fabricated case citations with the same confidence as legitimate ones. Lawyers report encountering entirely fictional cases — invented parties, plausible-sounding holdings, case numbers that match real formatting but correspond to nothing. The AI engages in pattern-matching, not verification.
Every piece of AI-generated legal content from a general-purpose model requires more verification than the underlying work would have taken to do properly in the first place. The result is counterproductive overhead, not genuine assistance.
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The AI workspace built for legal work
Dictate, draft, and organise your cases — with full data sovereignty and no prompt engineering required.
Try Whisperit free →A different philosophy: AI assists, lawyers decide
Whisperit was designed around a single principle: the lawyer is always the expert. AI systems are statistical models with inherent limitations. The question is not what they can generate — it is what you can trust.
Whisperit's AI handles non-judgment tasks: transcription, formatting, extraction, translation, and organisation. It does not generate legal opinions, fabricate citations, or produce content that requires a lawyer's verification to be safe to use.
- Transcription: converting dictation to structured text with legal vocabulary
- Formatting: organising documents to your house style
- Extraction: pulling contract terms, parties, and dates from uploaded documents
- Translation: multilingual rendering that preserves legal terminology and formal register
- Organisation: automatic case file categorisation and matter linking
Transparent about limitations
When Whisperit's AI is uncertain, it says so. The most dangerous AI is the one that does not know its boundaries. A tool that acknowledges uncertainty enables review. A tool that presents everything with equal confidence makes verification effectively impossible.
The right evaluation criterion for legal AI is not capability breadth — it is trustworthiness. What can this AI do that I can actually rely on?