Published 2025-04-17
Leah is ContractPodAi’s agentic AI assistant, now available as a stand-alone product, which enhances the way legal documents are reviewed, analyzed, summarized, created, and interconnected, offering a comprehensive solution for legal use cases. In a recent interview, Sarah McLaren, a Sales Engineer at ContractPodAi, discussed the problems Leah solves, how it incorporates AI, and what sets it apart from the competition.
Published 2025-04-15
Legal tech is no longer a niche area in the legal industry, and insisting on maintaining the rigid siloes of yesteryear only hampers innovation.
Published 2025-04-14
In a recent survey that Legaltech Hub (LTH) delivered with the organizing committee for the Strategic Knowledge and Innovation Legal Leaders Summit (SKILLS), 100 top tier firms responded to a series of questions about which generative AI (GenAI) technologies they were actively using, what they were piloting, and which technologies they were considering licensing in the future.
Published 2025-04-11
QorusDocs is an AI-powered proposal management software that automates the creation of personalized pitches, proposals, and RFP responses. In a recent interview, CEO Ray Meiring discussed the problems QorusDocs solves, how it incorporates AI, and what differentiates it in the market.
Published 2025-04-10
In a recent survey that Legaltech Hub (LTH) delivered with the organizing committee for the Strategic Knowledge and Innovation Legal Leaders Summit (SKILLS), 100 top tier firms responded to a series of questions about which generative AI (GenAI) technologies they were actively using, what they were piloting, and which technologies they were considering licensing in the future.
Published 2025-04-10
In a RAG pipeline, hallucinations can arise at three critical stages: before retrieval, during retrieval, and during generation. Imagine all the things that could go wrong during a library visit—asking for the wrong book title, picking the wrong shelf, or misunderstanding the content—and you'll have a good analogy for how these issues manifest in a RAG pipeline.
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