{"id":23524,"date":"2025-03-19T12:51:20","date_gmt":"2025-03-19T12:51:20","guid":{"rendered":"https:\/\/www.airony.ai\/staging\/?post_type=neuros_case_study&p=23524"},"modified":"2025-04-10T20:29:27","modified_gmt":"2025-04-10T20:29:27","slug":"automated-contract-manager","status":"publish","type":"neuros_case_study","link":"https:\/\/www.airony.ai\/en\/case-studies\/automated-contract-manager\/","title":{"rendered":"Automated Contract Manager"},"content":{"rendered":"
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Automated Contract Manager<\/span><\/h1><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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The challenge<\/span><\/h2><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Every company needs to monitor key information relating to existing contracts with suppliers and vendors, such as: amount spent, remaining contract capacity, unit prices applied for specific goods or services, and the availability of similar contracts.<\/strong><\/p>

These monitoring activities are typically performed manually by contract managers, accessing company systems and retrieving data one by one. The result is a slow, fragmented, and inefficient process that prevents an integrated and timely company-wide view.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The solution<\/span><\/h2><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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An intelligent platform that, using Natural Language Processing (NLP) technologies and Business Intelligence tools, automatically extracts critical information from all company contracts, organizing it in a structured and easily accessible way. The system also provides predictive analytics and monitoring tools for proactive contract management.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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  • Automatic classification and categorization of existing contracts, based on information extracted via AI NLP.<\/li>
  • Creation of a centralized and automatically updated database with key data (e.g., contract dates, unit prices, remaining capacity, suppliers, amendment possibilities).<\/li>
  • Processing and presenting structured data using an AI engine, with cash flow projections, critical KPIs, and a risk and deadline alert system.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence.<\/p>CEO of IBM<\/cite><\/blockquote><\/figure>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    The benefits<\/span><\/h2><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    The solution centralizes and streamlines contract management, improving transparency, operational efficiency, and decision-making capabilities across the company. All information becomes easily accessible and usable to optimize processes and prevent risks.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    • Instant access to all relevant information for each contract, improving speed and accuracy in operational decisions.<\/li>
    • Simple and intuitive comparison between all contracts in the same product or service category, facilitating optimization and rationalization.<\/li>
    • Timely and on-budget management of the entire contract portfolio, preventing material shortages and minimizing critical issues.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

      Every company needs to monitor key information related to existing contracts with suppliers and vendors, such as: amount spent, remaining contract capacity, unit prices applied for specific goods or services, and the availability of similar contracts. These monitoring activities\u2026<\/p>","protected":false},"author":6,"featured_media":23764,"template":"","neuros_case_study_category":[],"neuros_case_study_tag":[59,63],"class_list":["post-23524","neuros_case_study","type-neuros_case_study","status-publish","has-post-thumbnail","hentry","neuros_case_study_tag-solutions","neuros_case_study_tag-urban"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/neuros_case_study\/23524","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/neuros_case_study"}],"about":[{"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/types\/neuros_case_study"}],"author":[{"embeddable":true,"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/users\/6"}],"version-history":[{"count":4,"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/neuros_case_study\/23524\/revisions"}],"predecessor-version":[{"id":23528,"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/neuros_case_study\/23524\/revisions\/23528"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/media\/23764"}],"wp:attachment":[{"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/media?parent=23524"}],"wp:term":[{"taxonomy":"neuros_case_study_category","embeddable":true,"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/neuros_case_study_category?post=23524"},{"taxonomy":"neuros_case_study_tag","embeddable":true,"href":"https:\/\/www.airony.ai\/en\/wp-json\/wp\/v2\/neuros_case_study_tag?post=23524"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}