Lantern powers 2 source-linked AI deployments documented in AIUseCaseHub, across 2 industries and 1 country. Documented deployments include AI agents, RAG.
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Agent Cases
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Filter Lantern's implementations by cloud provider evidence.
How Lantern builds AIBuild, Buy & Compose — what they mean
A leading academic life sciences university faced fragmentation of its data sources, impacting operational efficiency and patient care.To address this, the institution turned to a sophisticated generative AI platform architected on Microsoft Azure technology, supported by Lantern, to centralize data and build a secure, unified knowledge base for researchers and clinicians.The system integrated Azure OpenAI, Azure AI Document Intelligence (OCR), AI Search, Azure Functions, and Azure SQL Database, allowing real-time ingestion and processing of millions of data points from diverse sources (websites, files, APIs).New AI assistants under development are tailored for specialized clinical needs, including clinical trial onboarding, application of clinical guidelines, and department-specific knowledge support.HIPAA compliance and robust governance ensured data security and ethical use, while customizable large language model interactions allowed safe, task-driven access to sensitive data.Results included over 1,000 daily users, 1 million+ endpoints ingested, enhanced research output, and a framework for ongoing AI agent and assistant expansion in healthcare.
Avocados From Mexico (AFM), a non-profit with more than 30 employees in the food sector, was experiencing bottlenecks and inefficiencies in its purchase requisition process, particularly for the marketing team working under tight deadlines.In 2017, AFM adopted SAP Business ByDesign but found the system complex and time-consuming for purchasing specialists. AFM needed a scalable solution to streamline this workflow and provide better visibility and process automation.Lantern, acting as an ad-hoc CIO, implemented Microsoft Power Platform, integrating with SAP for seamless requisition approval and data reconciliation. Dataverse was leveraged for the approvals process while Power BI and Microsoft Fabric were used for analytics and data-driven insights.The transformation enabled faster, mobile, and user-friendly approvals, drastically reducing errors and the workload for purchasing staff.The process time dropped from 15 minutes to less than 1 minute, resulting in monthly savings of 34.5 hours, enhanced visibility, and greater operational efficiency.Teams and Outlook integrations are planned to further improve the workflow.Lantern continues to support AFM with further projects in automation, data analytics, invoice processing, and AI-driven automation initiatives.