How AI can supercharge contract search

Searching for contracts can be arduous, but we now have AI-powered Natural Language Search (NLS) to lighten the load. In this blog, we will explore the effective utilization of artificial intelligence (AI)’s natural language search for locating contracts. By employing AI-driven technology, you can effortlessly navigate through vast repositories of legal documents — making contract search much faster and less painful.

What is AI natural language search?

According to EY, 90% of contracting professionals say they face challenges trying to locate contracts. NLS can help eliminate this problem.

The concept of NLS is centered around utilizing AI technology to facilitate seamless navigation through extensive information repositories. With this approach, users can effortlessly access and retrieve relevant data like key clauses and provisions by inputting specific keywords or phrases into the search function.

Leading enterprise tools utilize AI technology to break down human language into fragments, aiding in extracting relevant information from contracts. Natural Language Processing (NLP) algorithms analyze the linguistic structure, syntax, and semantics of the text—all of which are important to overcome challenges in processing difficulties surrounding poor contract writing.

Through a comprehensive analysis, accurate and pertinent results are generated, enabling individuals to locate the information they need efficiently and ensuring the process of searching for information becomes streamlined and intuitive, saving time and reducing the risk of missing critical information.

Here are some ways contracts can now be analyzed efficiently and accurately, simplifying the process of retrieving vital information.

Extraction of key clauses

The extraction of key clauses in contracts, such as payment terms, confidentiality agreements, and termination clauses, can be achieved by utilizing AI models. By automatically identifying and extracting these critical clauses, businesses can swiftly review and comprehend the fundamental elements of a contract.

Named Entity Recognition (NER)

NER is a technique used in NLP to identify and classify named entities in text. These entities can include names of people, organizations, locations, dates, and more. The process involves analyzing the structure and context of the text to extract meaningful information, enabling CLM systems to enhance contract indexing, utilize quick search and retrieval, and facilitate accurate contract analytics.

Contract classification

Contract classification allows for the categorization of contracts based on their content and structure. By analyzing textual patterns and semantic features, NLP enables the identification and organization of contracts into relevant categories without relying on manual intervention or human effort.

Language translation

Do you need conversion of contracts from one language to another? The process of translating languages is made possible through the utilization of advanced algorithms and linguistic models. NLP’s language translation capabilities enable the seamless communication and comprehension of content across diverse linguistic boundaries.

Managing compliance challenges with natural language search technology

What’s more, compliance challenges can be effectively managed by utilizing natural language search technology. With natural language processing algorithms, relevant information can be extracted and analyzed from vast amounts of data, enabling a comprehensive understanding of regulatory requirements.

Through this implementation, valuable insights can be gained, facilitating the development of robust compliance strategies. Compliance challenges are efficiently tackled by employing natural language search technology, ensuring adherence to legal obligations, and mitigating potential risks.

Identifying NLP applications for contract searches

The utilization of NLP applications has led to significant advancements in the field of contract management: document categorization and search features have been greatly improved, resulting in faster and more accurate results that free up contract managers from annoying, repetitive tasks. Valuable insights into the transformative impact of NLP in contract management can be found within the right AI solution platform, if one knows what to look for:

How wide is the machine learning comprehension of how you phrase your queries?

How are your search queries answered, and is it easy to understand and process the answers?

Is there more than one way to access the NLS function?

These are some things to remember about an ideal NLP solution, especially beyond the main feature of contract summarization.

The future of NLP in contract search

NLP is always evolving and businesses can continue to learn from its usage as well. Invaluable insights in better payment terms, better pricing structures, or ideal service offerings are provided by NLP for contracts through the analysis of patterns, trends, and user behavior within contracts. These analytical capabilities allow businesses to identify areas that can be improved, optimize contract terms, and enhance negotiation strategies. The continuous improvement facilitated by NLP ensures that contract management processes remain agile and effective.