
Founded by Sean Safahi & Chenyu Li
Many legal practice areas - including litigation, M&A, and insurance - routinely deal with large document sets, and attorneys spend many hours reviewing those documents to get the information they need.
In an age of AI, law firm clients demand both increased efficiency and improved effectiveness.
Existing technology solutions, like eDiscovery platforms, don’t help attorneys understand the information that exists inside the documents. They’re costly, cumbersome, and their search is difficult to use to pinpoint the relevant information.
So, attorneys rely on manual document review, which is even more costly, prone to human error, and difficult to get client budget buy-in.
Abel allows attorneys to get the depth of manual review at the scale of technology. Attorneys import legal records of a variety of document formats, types, and sizes.
Abel leverages a proprietary entity extraction to process the documents and uncover a structured representation of the information contained in them. The platform's extraction pipelines are flexible and can be customized to identify the relevant entities to customer needs, which can include things like:
Attorneys use Abel to explore the extracted entities and to examine the relationships between them. This allows them to answer more complex questions with more nuance than existing solutions.
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