📰 Key Takeaway

Lithuanian legal tech company Legora integrated OpenAI’s latest GPT-6 Astra model into its financial statement review workflow, and testing showed the system completed a 41-document review in minutes, catching all four intentionally planted errors, with review performance improving nearly 40% over the previous setup. See the original article for full details.

💬 JudyAI Lab Take

Lithuanian legal tech company Legora rolled GPT-6 Astra, OpenAI’s newest model, into its financial statement review workflow — and the results are worth a look for any AI builder. It processed 41 documents in just a few minutes, caught all four intentionally planted errors, and improved review performance by nearly 40% over the previous setup.

What this case really shows isn’t just “the model got better” — it’s that review-type tasks are becoming a concrete landing spot for legal AI in production. Compared to content generation, review tasks have a clear right-or-wrong answer (did it find the error or not), which makes the results easy to quantify and easier for enterprise clients to trust and adopt. For AI builders, this points to a product direction: instead of building a vague “smart assistant,” find a vertical workflow with clear acceptance criteria (like document review or contract comparison), turn AI accuracy into a measurable business metric, and it becomes a lot easier to get enterprises to pay.

If you’re building something similar, start by mapping out which review-type tasks in your domain have a “correct answer” — that’s your first entry point for putting AI into production.

📅 Original Source

🔗 Further Reading