DoNotPay · IBM, Facebook
more than 86,000 — Number of users
Independently reportedProfessional services · Legal review · NLP · Scaled
Legal review
Vitesco Technologies · blu BEYOND
Vendor-reportedAutomotiveScaledLLM
Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.
Reported by blu-beyond.com (vendor self-report). Checked against the source page on 2026-09-06. 3 of 3 figures below appear on that page word for word.
The problem
Vitesco Technologies wanted to find out if AI could simplify the demanding legal contract reviews and achieve more efficiency in contract handling.
What was deployed
- Vendor
- blu BEYOND
- Products
- Azure, Qdrant, Mistral
- Models
- Mistral
- Technique
- LLM
- Build or buy
- Built in-house or to order
- Deployment
- Custom build
- Data used
- highly sensitive data, domain-specific company knowledge, supplier/customer contracts, legacy contracts
- Scale
- 40.000 + contracts now integrated into the solution
- Timeline
- 3 months
What changed
Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.
Up to 80%reduction in contract review time
“Up to 80% reduction in contract review time”
Quoted word for word from the source · round percentage, no baseline given
Less than 3 monthstime to MVP completion
“Less than 3 months to MVP completion”
Quoted word for word from the source
40.000 +contracts integrated into the solution
“40.000 + contracts now integrated into the solution”
Quoted word for word from the source
“The potential of generative AI is enormous. At Vitesco Technologies, we saw real opportunities, especially in contract management. This use-case-driven approach helped us take strong first steps. The insights we’ve gained on LLMs, prompting, and automation are now driving AI adoption across the entire company.”
Difficulties and limits
- Missing standards & benchmarks
- Contracts come in many forms—with varied structures, layouts, and contexts
- Developing a structure to make contracts machine-readable and analyzable using an LLM
Sources
- blu-beyond.com — vendor self-report
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