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Canotera Canotera provides AI-powered predictive analytics for legal disputes, bringing transparency and efficiency to the legal industry. Using Large Language Models and Geometric MachineLearning, our platform forecasts litigation outcomes at scale. Its simple to adopt no lengthy implementation or training required.
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. Our model emulates the actual legal reasoning, evaluative, and analytical skills taught to attorneys. What problem do you solve?
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. Demo video: [link].
Users host meetings, mediations, and depositions that mimics real-life litigation scenarios and provides a level of security befitting legal proceedings. Catylex Contract Analytics Elevator Pitch: For businesses that depend on contracts, Catylex Contract Analytics delivers quick answers without reading mountains of paper.
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. Demo video: [link].
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. Our platform is the only one that learns your story (or your opponent’s) and has the power to efficiently deliver the best possible results.
I guess because it’s a machinelearning technology, you can ask it the same question and get different answers. I was reading Framers: Human Advantages in an Age of Technology and Turmoil , in which it discussed the machinelearning car company Waymo. We tend not to create information so much as mediate access to it.
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