Enhancing radiation oncology workflows
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Mayo Clinic uses Meta's Llama 2 to develop RadOnc-GPT, a specialized large language model for radiation oncology. RadOnc-GPT is fine-tuned on patient records and deployed locally to ensure data security. It supports a chatbot that answers routine post-radiotherapy questions, reducing nurses’ and clinicians’ workloads and improving treatment decision-making speed, accuracy, and quality. Future developments include predicting patient outcomes and expanding clinical tasks, enhancing operational efficiency and patient care.
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Reduces nurses’ and clinicians’ workloads and improves treatment decision-making speed, accuracy, and quality.
77
AI use cases in
Healthcare
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Cactus Life Sciences implemented Microsoft 365 Copilot to automate routine tasks and augment the generation of scientific content under human oversight. They integrated the tool into their Microsoft 365 workflows to assist with drafting, editing, and approving complex scientific communications, streamlining content creation and dissemination processes. This approach improved the efficiency of internal content workflows enabling faster communication of critical scientific data to stakeholders.
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Indegene integrated Microsoft 365 Copilot into its suite of productivity tools, including Word, Excel, PowerPoint, Outlook, and Teams, to automate routine email responses, document summarization, data analysis, and RFP development. The solution was implemented across departments such as content, pre-sales, finance, and project management, ensuring stringent data security and privacy standards while streamlining critical business workflows.
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Ontada leveraged Microsoft’s Azure OpenAI Service Batch API and Azure AI Foundry to build its ON.Genuity platform, which processes 150 million unstructured oncology documents to automatically extract nearly 100 critical data elements across 39 cancer types. They integrated the new platform with their structured iKnowMed system using Azure Databricks for data ingestion and Azure Document Intelligence for text extraction, transforming manual chart review processes into an automated workflow that supports clinical decision-making and life science product development.
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151
companies using
Data Agents
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wealthAPI implemented a next‐gen contract detection solution by integrating DataStax Astra DB on Google Cloud and leveraging Google Gemini models for AI‐powered analysis. They deployed DataStax’s vector search and real‐time insights capabilities to scale contract detection across millions of users in less than three months, streamlining wealth management workflows by dramatically reducing response times and efficiently handling massive data volumes.
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Aura Intelligence integrated Anthropic's Claude via Amazon Bedrock into its data pipeline to automatically classify over 200 million job titles and industry pairings from multi-language data, replacing manual lookups and fuzzy matching. They fine-tuned foundation models on proprietary datasets and leveraged AWS infrastructure, including SageMaker and prompt management, to automate QA, report generation, anomaly detection, and real-time hiring trend analysis.
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LaunchNotes leverages Claude in Amazon Bedrock in their product 'Graph' to transform engineering data into actionable insights. Graph functions as an ETL platform with Claude managing data pipelines, helping engineering managers understand development metrics, reduce incident identification time, automate updates, and generate customized release notes and technical documentation.
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49
solutions powered by
Meta
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Roboflow uses Meta's Segment Anything Model (SAM) to enable users to automatically segment objects in images and videos, significantly reducing the time required to create training datasets for computer vision models.
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Untukmu.AI, an online gifting site in Indonesia, uses Meta's Llama 3.1 8B model with split inference processing to protect customer privacy. By running part of the AI model on customers' devices and the rest on their servers, they deliver personalized gift recommendations without accessing or storing personal data. This ensures customer privacy while still providing high-quality, tailored suggestions, enhancing trust and satisfaction.
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CodeGPT, a popular coding assistant with over 1.4 million downloads, integrates Meta's Llama models to enhance developer productivity. By using Llama 3.2 (90B), CodeGPT helps developers not just generate code but also answer questions about their codebase, debug code, and onboard new team members. It includes a codebase graph mechanism that lets Llama understand entire repositories, allowing developers to effectively "talk" with their code. This integration leads to at least a 30% increase in productivity and accelerates onboarding from months to days.
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284
AI use cases in
North America
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Cox Automotive integrated Claude via Amazon Bedrock into its portfolio by first creating a sandbox environment to evaluate performance metrics and then selecting Claude 3.5 Sonnet for complex tasks and Claude 3.5 Haiku for high-volume content generation. They automated personalized dealer-consumer communications, generated engaging vehicle listing descriptions, and produced SEO-optimized blog posts, while also streamlining internal data governance through automated metadata generation. This integration optimized operational efficiency across marketing and internal data processes.
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Intuit integrated Google Cloud’s Document AI and Gemini models into its GenOS platform to automate the autofill of ten common U.S. tax forms, including complex 1099 and 1040 forms. The solution extracts and categorizes data from uploaded documents, drastically reducing manual data entry for TurboTax customers. This integration streamlines tax preparation workflows and improves speed and accuracy.
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Block implemented Anthropic’s Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) on its Databricks platform to power its internal AI agent, codename goose. They integrated the LLM using secure OAuth-enabled connections and a custom MCP server to connect internal databases and tools, enabling employees across all roles to auto-generate SQL queries, analyze complex data, and automate workflows. This agentic integration streamlined software development, design prototyping, and data analysis by translating user intents into actionable insights.
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