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This post is the third in a series about how to implement legal AI that knows your law firm. In the series, we cover the differences between LLMs and search, the elements that make a good search engine, the building blocks of agentic systems (e.g. RAG), and how to implement a system that is fully scalable, secure, and respects your firm’s unique policies and practices.
Retrieval Augmented Generation (RAG) bridges the gap between large language models and your law firm’s data. Learn how this technique boosts precision, reduces hallucinations, and creates smarter, more contextual AI systems.
In our latest team spotlight, JJ shares what drew her to DeepJudge, how she thinks about AI in law, and why the best legal tech starts with listening to the lawyers who serve real people.
Discover why using standalone LLMs as search engines in legal practice is risky. Learn how retrieval-augmented generation (RAG) systems offer safer, firm-specific AI solutions.
DeepJudge will be at ILTACON 2025 from August 10-14 at the Gaylord National Resort and Convention Center in National Harbour, Maryland.
DeepJudge will be at LegalTechTalk from June 26-27 at the InterContinental O2 in London
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