QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
A global pharmaceutical manufacturer must rigorously evaluate manufacturing deviations, such as machine stoppages or foreign material contamination, to determine whether production batches are safe for shipment.
Quality assurance teams struggled to manually search massive databases of past incidents to determine the correct response strategy. The evaluation...
“過去の類似事例をもとに網羅的な検索を行い、情報にもとづいた最適な対応方針を選択することが理想だが、現状では、過去の逸脱事例として大量の情報が登録されているため、これらを網羅的に検索し、一次整理するのが困難であり、時間がかかるという課題があった。その結果、熟練者の知見に依存することになったり、対応方針の決定までに多くの工数と時間がかかったりしていた。”
Global pharmaceutical company specializing in oncology, immunology, and gene therapy.
Provided Microsoft Azure, Azure OpenAI Service, and Azure AI Search to build a multi-agent AI environment for processing manufacturing deviations.
Astellas Pharma's Manufacturing quality assurance is part of this use case:
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QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
A global pharmaceutical manufacturer must rigorously evaluate manufacturing deviations, such as machine stoppages or foreign material contamination, to determine whether production batches are safe for shipment.
Quality assurance teams struggled to manually search massive databases of past incidents to determine the correct response strategy. The evaluation...
“過去の類似事例をもとに網羅的な検索を行い、情報にもとづいた最適な対応方針を選択することが理想だが、現状では、過去の逸脱事例として大量の情報が登録されているため、これらを網羅的に検索し、一次整理するのが困難であり、時間がかかるという課題があった。その結果、熟練者の知見に依存することになったり、対応方針の決定までに多くの工数と時間がかかったりしていた。”
Global pharmaceutical company specializing in oncology, immunology, and gene therapy.
Provided Microsoft Azure, Azure OpenAI Service, and Azure AI Search to build a multi-agent AI environment for processing manufacturing deviations.
Astellas Pharma's Manufacturing quality assurance is part of this use case:
Related implementations across industries and use cases
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
Identifying materials required manually scouring intricate drawings. AI now extracts specs into a database for instant search.
Organizing tens of thousands of compliance documents bottlenecked audits. Now, AI structures files and drafts summaries for expert review.
Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
Manual scheduling trapped recruiters in logistics. AI now automates interview coordination, freeing teams for strategic work.
Agencies slowed localization for 90 markets. Now, AI drafts marketing copy, and native speakers verify clinical precision.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.