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Marking its second acquisition this year, the cloud practice management company SurePoint Technologies has acquired Coyote Analytics , a company that provides practice management, financial management and business intelligence software for law firms. The future is analytical insight driving embedded prediction.”
Evisort uses machinelearning and natural language processing to power its core product, which it calls its Contract Intelligence Platform, and which integrates a contract repository, contract lifecycle management, and contract analytics. Read more about Onit on the LawNext Legal Tech Directory.
In the ABA 2020 Legal Tech Survey , 23% of law firms reported not being interested in AI, while 34% said they didn’t know enough about AI to speak to their firms’ interest. That doesn’t mean, however, that law firms and litigation support teams have been quick to embrace them. AI Hesitation.
How we’re unique: While other products are descriptive in nature, we are building the first truly prescriptive set of legal analytics products. We can help lawyers make evidence-based decisions by providing custom-tailored recommendations and analytics, all focused on judges and their philosophies of the law. Founded: 2/20/2020.
OpenText provides Axcelerate Cloud users with the opportunity to leverage Generative AI for case and concept label summarization Building on a long tradition of incorporating AI and machinelearning to speed document review OpenText is thrilled to introduce the next generation of AI-enhanced productivity - Aviator for Axcelerate.
Demo video: [link] Founded: 10/28/2020, Vancouver, BC, Canada Target customer: Solos, small and medium size firms. We exploited how essential story elements fit into any investigation or discovery process and made highly complex analytics fit naturally with the way legal professionals want to find answers in ESI. Demo video: [link].
OpenText eDiscovery solutions have a long history of incorporating artificial intelligence (AI) and advanced analytics to dramatically improve review efficiency and lower costs while ensuring defensibility of process. Axcelerate drives down the cost of eDiscovery through analytics and automation. Axcelerate CE 21.2 Axcelerate CE 21.2
How we’re unique: While other products are descriptive in nature, we are building the first truly prescriptive set of legal analytics products. We can help lawyers make evidence-based decisions by providing custom-tailored recommendations and analytics, all focused on judges and their philosophies of the law. Founded: 4/1/2020.
Demo video: [link] Founded: 10/28/2020, Vancouver, BC, Canada Target customer: Solos, small and medium size firms. We exploited how essential story elements fit into any investigation or discovery process and made highly complex analytics fit naturally with the way legal professionals want to find answers in ESI. Demo video: [link].
Also announced: The launch of Lexis+ UK, the UK version of the premium research service the company released in 2020 in the U.S. The APIs provide access to 99% of LexisNexis content, spanning legal, news, court dockets, business and analytics, all enriched through LexisNexis’s classification and normalization process.
The growing use of legal analytics is rapidly transforming the practice of law. Within law firms, analytics drive litigation strategy, business development efforts, and hiring decisions. Within corporate legal departments, analytics drive outside counsel hiring and internal business operations.
The term “automated employment decision tools” is broadly defined as any “computational process, derived from machinelearning, statistical modeling, data analytics, or artificial intelligence” that “issues a simplified output.” Hopefully the full scope of the AEDT will be made clearer in the forthcoming rulemaking process.
AI-assisted discrimination “Machinelearning is like money laundering for bias.” – Maciej Cegłowski [7] Employers can use AI to assist with a host of tasks. 18] Maryland enacted a similar statute in 2020, requiring employers to obtain a job applicant’s consent before using AI-assisted facial recognition technology during interviews. [19]
As financial institutions increasingly deploy artificial intelligence (“AI”), including machinelearning and automated decision-making technologies, across their business lines, U.S. Gensler also raised the need to prevent analytics from “reinforc[ing] societal inequities that may be embedded in data,” thereby deepening bias.
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