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Evisort Enhances AI Leadership with Advanced Contract AI

Evisort

Enhanced AI engine streamlines contract risk assessment, business analysis, and value optimization with customizable AI

Evisort, the leader in AI-native contract intelligence and contract lifecycle management (CLM), announced enhancements to its proprietary AI engine that empowers customers to ask anything and track everything in their contracts to drive high-value business outcomes. The newly-enhanced Evisort AI engine intelligently orchestrates its application of traditional and generative AI tools — including the Evisort LLM — to achieve the most accurate, scalable results for any contract management use case.

Evisort’s first-to-market AI orchestration functionality enables users to derive maximum value from AI without needing technical skills or training, making Evisort’s AI customization solution, Document X-Ray™, even more powerful and easier to use. Before publishing any new AI model, Document X-Ray now runs hundreds of experiments in seconds to optimize performance. It selects the best large language model (LLM) for each specific request from among the proprietary, contract-specific Evisort LLM and a number of best-of-breed generic LLMs leveraged directly in the Evisort platform.

Notably, this patent-pending technology also recommends optimized language for each AI prompt to achieve the most accurate results, as gauged by a simple user feedback experience. This innovative use of AI ensures that Evisort customers gain the greatest possible value without technical skills or training. By delivering customers unparalleled precision and efficiency, Document X-Ray sets a new standard in AI customization.

Launched in January 2024, Document X-Ray not only extracts contract terms at any level of granularity but can also generate data points beyond the “four corners” of the contract – such as calculating important dates and amounts, summarizing key terms in plain language, and assigning rankings, ratings, and classifications. Unlike CLM products that are limited to static, pre-trained AI models, Evisort’s Document X-Ray makes contract AI fully customizable to meet the needs of diverse business teams across any industry.

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“Users of AI-powered products shouldn’t have to be specialists or prompt engineers to get highly reliable results from their AI, nor should they be limited to just one generative AI technology,” said Amine Anoun, Evisort co-founder and CTO. “At Evisort, we’re proud to deliver responsible, cutting-edge AI that’s democratized for everyday users on legal and business teams at some of the world’s largest corporations.”

Customers of Evisort’s contact intelligence platform can ask anything about their contracts and get clear, sourced answers via a simple, conversational experience. They can limit the scope to specific documents or groups, or apply their questions to all contracts across their repository at once. Evisort’s Document X-Ray, in turn, converts those questions to custom AI models that automatically track everything the organization cares about across all contracts and related transactional documents, like POs, invoices, and SOWs.

As part of its latest enhancements, Evisort users can also now save, group, and share their questions across teams. This new capability effectively empowers users to build a virtual playbook for contractual compliance just by asking questions, enabling flexible yet comprehensive risk assessment of agreements both before and after signature.

Evisort has leapfrogged the CLM space with next-generation contract AI. It’s the fastest to deploy, most field-tested, most secure solution in the market,” said Justin Hectus, Managing Director and legal process automation expert at Harbor, which serves 50% of the Fortune 500 and 80% of Am Law 200 law firms. “With Document X-Ray, we’re not only able to help our customers do what they did before faster, but also do things they could never do before, like responding to changing market conditions and industry-specific challenges quickly and easily.”

Source: PRNewswire

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