ayfie, a newcomer at this year’s ILTA show just announced the integration of ayfie Inspector with the Relativity product.

While so many new technologies claim using “Artificial Intelligence” (AI), Deep Leaning or machine learning magic to aid in document review, the ayfie team has done something different. They aimed to improve search results delivered during the eDiscovery process by asking; “What do the words really mean?”

The issue lies in how machines read queries and the results that are returned. Using contract review as an example, taking thousands of documents, if individual tokens are indexed by software and then returned based on matching keywords then the intent of the query is often detached from the results. ayfie Inspector leverages a codified understanding of natural language to find relevant parts of the contracts and focus the search on those.

Leverage the Power of Linguistic Identification

ayfie analyzes the linguistic significance of phrases, concepts, entities or sections of text then builds an index of key Features that translate into more relevant matches for the user. With identification of core semantic facts (eg. clause Identification for contracts, identification of PII, PHI), ayfie Inspector can facilitate specific workflows within Relativity to tackle processes involved in, for example, M&A DD or GDPR Compliance.

Standard eDiscovery processes like de-duplication, email threading, clustering and classification are all enhanced by ayfie’s linguistic feature engineering methodology. ayfie Inspector delivers the right information to the user to eliminate redundant efforts.

Enriched Contract Meta-Data Amplifies Relativity Search Results

The integration of ayfie Inspector and Relativity gives users the ability to apply ayfie’s range of capabilities to fields within Relativity. Contract review challenges are tackled seamlessly by taking the ambiguity out of terms which are often generic, similar or buried in long complex documents. Let’s say you want to search for “breach.” Standard results return anything with the word breach. Now, results delivered could be specific to the presence of “breach” in a confidentiality clause.

By extracting key core semantic facts, such as Contracting Parties and isolating clauses from documents, ayfie allows for deeper analysis of contractual data. For example, enabling a near-dupe analysis on specific clause types so users can quickly identify language which diverges from the standard template. The power of grouping contracts based on timelines, categories or value allows reviewers to quickly prioritize the documents.

Summarization and Reports

After the review process is complete, you can view the data, make tagging decisions and produce a report for the client. An elegant cover sheet or quick reference guide can be used to swiftly share the contract review opinion.

In Closing 

The use of ayfie’s style of Aided-Intelligence (ai) is growing, particularly in use cases that require a higher degree of precision. ayfie Inspector’s application of Linguistic Identification increases the relevancy of results, making it a significant innovation in the eDiscovery marketplace. The platform has the potential to uncover more relevant information in a fraction of the time of traditional approaches and as advancements in contract review process become readily available.

Learn more about ayfie Inspector for Relativity®here.

Chelsey Lambert

Chelsey Lambert

Chelsey Lambert is a Legal Technology Specialist, published Author and CLE Speaker. As a former Practice Management Advisor for the Chicago Bar Association, and Vice President of Marketing for a leading case management provider she has seen our industry from many angles. Today, she works with vendors to bring their products or emerging technologies into the marketplace. And, teaches legal technology courses to lawyers all over the country sharing different ways technology can benefit their law firm. As Founder of Lex Tech Review and Lex Tech Media Group she welcomes the opportunity to chat!

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