We are starting our quest for general artificial intelligence by designing a model that will help in-house lawyers assess risk. Our proprietary software (still in development) structures all legal information on the federal level and ties it to unique risk factors of our clients. This empowers in-house attorneys to see issues quicker or that were once hidden and expands their knowledge base to address these issues by giving them transparent and well structured access to the rules that govern their clients actions. We seek to empower the generalist to dive deeper into any practice area quickly and effectively so they can reduce their reliance on outside sources and craft unique solutions.
Simon Says is a website that securely transcribes your confidential audio/video files in minutes with speech recognition. Users can then share projects within teams and search, annotate, and export them. We help lawyers significantly increase efficiency by accurately transcribing interviews, calls, and court recordings, allowing them to focus on the meaningful dialogue.
Klarity uses Artificial Intelligence to review sales contracts under your company legal policy. Klarity pulls contracts from your emails and databases and returns them reviewed in a Word format with annotations and redlines along with a summary. Your company experiences accelerated sales and higher compliance without having to think of contract review anymore. Klarity was founded by Andrew Antos, a Harvard lawyer with experience from BigLaw, and Nischal Nadhamuni, a MIT Computer Science graduate with background in Artificial Intelligence. You can read Klarity's full story here and here.
SpeedLegal SaaS platform helps founders, angel investors and SMBs instantly understand their contracts, clarifies each clause, and verifies that each term complies with market standards.
The semantic modeling of clauses and texts - aka understanding the meaning of clauses - enables the system to assess the clauses and contracts holistically. It allows a direct comparison of contracts based on their meaning rather than on the actual wording. Using this technology, the system can come up with similar clauses during writing, highlight duplicates and potential contradictions. Another use case is to automatically process, understand, route, and compare incoming documents with internal standards. Additionally, the semantic processing of contract text through AI can help by detecting inapplicable, missing information, and unclear formulation as depicted below. The system suggests potential flaws in clauses and makes optimization suggestions to the editor of the contract. The system is provided as micro services and can therefore integrate into any given (computerized) process within a law firm. We are aware of the fact that there is no standard for the legal domain rather than historically developed internal “standards” for software usage per each law firm/practise.