Use cases

DoorDash is a leading local commerce platform connecting consumers with restaurants, grocers, and retailers at massive scale. Its marketplace powers fast, on-demand delivery across food, convenience, and everyday essentials. With Zilliz Cloud(fully managed Milvus), DoorDash supports semantic search and recommendation. This helps match users with more relevant items and improves discovery across its catalog.

Reddit is a large-scale social platform built around user communities, conversations, and interest-driven content across entertainment and many other topics. Its network connects millions of users through constantly updated discussions and media. With Milvus, Reddit could power semantic retrieval across posts, comments, and media. This would help improve content discovery and relevance.

Doximity is a leading healthcare platform serving over 3 million U.S. clinicians with workflow, communication, and AI tools. Its products help doctors access information, collaborate, and work more efficiently across care settings. With Zilliz Cloud(fully managed Milvus), Doximity could power semantic retrieval across medical content and workflow context. This would help clinicians find relevant information faster.

IBM is a global AI and enterprise software leader, with platforms spanning application development, automation, and foundation models. Its AI stack helps organizations build and deploy production-grade assistants and copilots. With Milvus, IBM can support code copilot retrieval over code, docs, and development context. This helps developers surface relevant information faster while coding.

Fiverr is a global marketplace for freelance and professional services, connecting businesses with talent across design, marketing, software, and more. Its platform supports large-scale service discovery, matching, and project-based hiring. With Milvus, Fiverr could power semantic matching across services, freelancers, and briefs. This would help improve discovery and relevance for buyers.

Deloitte is a global professional services firm serving enterprises across audit, tax, consulting, and risk. Its teams help organizations manage complex operations, compliance, and digital transformation at scale. With Zilliz Cloud(fully managed Milvus), Deloitte could power semantic retrieval across knowledge, policy, and client workflow context. This would help teams find relevant information faster.

Naver is a leading internet services company in South Korea, operating large-scale platforms across search, content, commerce, and digital services. Its products serve millions of users through rich information and everyday online experiences. With Milvus, Naver supports retrieval for knowledge-intensive AI experiences. This helps improve relevance and speed across knowledge-based search and assistance.

IKEA utilizes Milvus for product recommendation, leveraging vector search technology to analyze customer preferences and match them with the most relevant products, enhancing the shopping experience through personalized suggestions.

Otter.ai leverages Milvus for Retrieval-Augmented Generation (RAG) to enhance Q&A functionality by efficiently sourcing and referencing relevant information from meeting transcripts, improving access to key insights and answers directly from recorded discussions.

Mozat leverages Milvus for Stylepedia's image search system, utilizing its capability for real-time, large-scale vector similarity searches across billions of datasets for garment detection, feature extraction, and refined post-processing, enhancing user experiences with functions like searching for similar clothing items, outfit suggestions, and personalized fashion recommendations.

Shutterstock enhances its "Search by image" feature by leveraging Milvus, enabling reverse image search capabilities that efficiently match user-uploaded images with similar content in their vast digital asset library.

Airbnb utilizes Milvus for its text-to-image search feature, enabling users to find rental listings by describing their desired features, such as "modernist building near the forest," through efficient vector search capabilities that match descriptive text with relevant property images.

Deepset incorporates Milvus into their Haystack framework to boost semantic search capabilities. Milvus enhances data indexing and similarity searches, supporting dynamic data management and integrating with multiple Approximate Nearest Neighbours libraries.

Exa is an internet services company building AI search infrastructure for developers and agents. Its platform combines web search, crawling, and retrieval to deliver fast, high-quality context from the open web. With Zilliz Cloud(fully managed Milvus), Exa could power semantic retrieval across indexed web content. This would help improve relevance and speed for AI search workflows.

Filevine is an AI legal SaaS platform for case management, legal CRM, and document-heavy workflows. It helps law firms and in-house teams work faster across complex matters and unstructured data. With Zilliz Cloud(fully managed Milvus), Filevine powers RAG over millions of legal documents. This helps attorneys retrieve relevant case information faster and reduce manual review time.

Poshmark employs Milvus for product recommendation, utilizing vector search to analyze user behavior and preferences, efficiently matching buyers with relevant fashion items, thereby personalizing and enhancing the shopping experience.

Salesforce's platform team uses Milvus to support a wide range of internal use cases, serving 100+ tenants with diverse applications and varying service levels, leveraging Milvus' vector search technology to enhance functionality and performance across their extensive ecosystem.

March Networks is a video surveillance and AI analytics company serving enterprise security and operations teams. Its platform combines cameras, cloud video management, and business intelligence for large multi-site organizations. With Milvus, March Networks could power semantic retrieval across video, events, and surveillance metadata. This would help teams investigate incidents faster.

Shell employs Milvus for multiple applications, primarily focusing on document search within a Retrieval-Augmented Generation (RAG) context, utilizing Milvus' vector search technology to enhance the accessibility and retrieval of documents in their vast corporate knowledge base.

Line utilizes Milvus to power its user-generated content (UGC) recommendation engine, enabling personalized news and music suggestions based on users' existing preferences through advanced vector search technology.

Zomato utilizes Milvus for its restaurant search functionality, leveraging vector search to analyze and match user queries with the most relevant dining options, enhancing the discovery process for users looking for specific restaurant experiences.

Palo Alto Networks utilizes Milvus for fraud detection, employing its vector search capabilities to analyze and identify patterns indicative of fraudulent activity, thereby enhancing the security and integrity of their networks and services.

SmartNews leveraged Milvus for its high-throughput, low-latency vector similarity search capabilities to efficiently match users with relevant ads in real-time, significantly enhancing ad recommendation performance and scalability.

Zigram employs Milvus for fraud detection by comparing real-time transactions against a database of known fraudulent activities, utilizing vector search technology to quickly and accurately identify potential fraud, enhancing security and trust in their operations.

Credal AI deployed Milvus on Amazon EKS to power semantic search in GenAI-driven workflows, enabling scalable, real-time processing of large datasets across diverse hosting environments, including cloud and on-prem setups.

The European Patent Office utilizes Milvus for patent search, leveraging its vector search capabilities to efficiently match queries with relevant patents, enhancing the precision and speed of patent retrieval and analysis.

Airtable is a leading platform for building collaborative apps and workflows on top of business data. It helps teams organize operations, automate tasks, and manage complex information at scale. With Milvus, Airtable could power semantic retrieval across records and documents. This would help users find related information faster in large workspaces.

Read AI is an AI note-taking and productivity platform that turns meetings, email, chat, and CRM activity into searchable summaries, insights, and next steps. It serves millions of users with conversational intelligence across everyday work. With Milvus, Read AI powers semantic search, AI agents, and RAG across billions of records. This delivered a 5× agentic search speedup while maintaining roughly 20–50ms retrieval latency for millions of monthly users.

Notta is an AI productivity platform that turns meetings, interviews, and conversations into searchable transcripts and actionable notes. It helps users capture, organize, and share spoken information more efficiently across everyday workflows. With Zilliz Cloud(fully managed Milvus), Notta powers semantic retrieval across large volumes of transcript data. This helps users find relevant content faster and improve AI search experiences.

Cisco is a global technology company known for networking, security, and enterprise infrastructure at massive scale. Its platforms support AI-ready data centers, connected workplaces, and digital resilience across industries. With Milvus, Cisco can support RAG across technical knowledge and enterprise context. This helps users retrieve relevant information faster and improve answer quality.

Compass utilizes Milvus for custom search by vectorizing floorplans, enabling the search for homes beyond traditional keyword matches and enhancing the property discovery process with advanced spatial and feature-based queries.

Shopee employs Milvus to enhance its real-time search capabilities, particularly in video recall, copyright matching, and video deduplication systems, leveraging Milvus' ability to efficiently handle billions of vectors and scale with data volume, thereby improving user experience and maintaining content integrity.

SoftBank Robotics Group is a global robotics and AI company focused on deploying intelligent automation in real-world operations. It acts as a robot integrator, helping enterprises use robotics data and systems more effectively at scale. With Zilliz Cloud(fully managed Milvus), SoftBank Robotics Group could power semantic retrieval across robotics knowledge, operational data, and workflow context. This would help teams find relevant information faster.

Beatoven.ai is an AI music generation platform that helps creators produce original, royalty-free soundtracks from text prompts. It serves more than 1.5 million creators and has generated over 6 million tracks. With Zilliz Cloud(fully managed Milvus), Beatoven.ai powers audio similarity search to retrieve matching loops during composition. This cut generation time by 2–3 seconds and reduced costs to about one-seventh of its previous setup.

Chegg employs Milvus for storing document chunks and embeddings to enhance document search capabilities, powering the homework help chat feature on chegg.com, thereby streamlining access to educational resources and assistance.

Farfetch employs Milvus as a vector database to support iFetch, its conversational AI for personalized shopping, by enabling real-time, accurate product recommendations through machine learning-generated product embeddings.

VerSe employs Milvus to enhance its recommendation engine for short videos by utilizing vector search to align viewer preferences with relevant video content, thus improving user engagement through personalized content suggestions.

Landing AI, founded by Andrew Ng, is a pioneer in Visual AI solutions, empowering industries to harness the full potential of visual data. By leveraging Milvus for image-based object detection, Landing AI enhances quality control in semiconductor manufacturing, specifically detecting disinfection in chip production processes. Using domain-specific Large Vision Models (LVMs) and Large Multimodal Models (LMMs), the platform ensures high accuracy and consistency in AI-driven inspections, transforming proof-of-concept AI projects into production-ready solutions.

Roblox's platform team utilizes Milvus to support a variety of internal use cases, with the most significant being avatar search, leveraging Milvus' vector search capabilities to efficiently match users with avatar options, enhancing the customization and user experience on the platform.

OpenEvidence is an AI medical platform that helps clinicians get fast, evidence-based answers to complex questions. Its search copilot synthesizes peer-reviewed research from leading journals into clear clinical guidance. With Zilliz Cloud(fully managed Milvus), OpenEvidence powers RAG over medical literature using vector embeddings. This helps match the most relevant journal passages and return cited answers with greater accuracy.

PLAUD AI is an AI note-taking platform that turns conversations, meetings, and voice recordings into searchable transcripts and summaries. Its products help professionals capture and use spoken information more efficiently across work. With Zilliz Cloud(fully managed Milvus), PLAUD AI supports chat and RAG over conversation data. This helps users find relevant context and answers faster.

eBay is a global e-commerce marketplace connecting buyers and sellers across a vast range of products and categories. Its platform supports large-scale product discovery, merchandising, and digital advertising. With Milvus, eBay can power ad recommendation using semantic similarity. This helps match users with more relevant sponsored products and listings.

New Relic is an observability platform that helps engineering teams monitor applications, infrastructure, logs, and digital experiences at scale. Its products turn telemetry into insights for faster troubleshooting and more reliable software. With Milvus, New Relic could power semantic retrieval across incident, log, and system context. This would help engineers investigate issues faster.

Grab employs Milvus for its food and restaurant recommendation system, utilizing vector search to analyze customer preferences and match them with relevant dining options, enhancing the user experience through personalized suggestions.

Rexera is a real estate operations platform that automates complex, document-heavy closing workflows with AI agents. Trusted by 350+ firms, it runs agents that manage over 10,000 tasks daily and process millions of pages each month. With Zilliz Cloud(fully managed Milvus), Rexera powers hybrid retrieval for AI agents across large transaction document sets. This improved retrieval accuracy by 40% and helped eliminate Elasticsearch from its search stack.

Bigo leverages Milvus for its efficient video deduplication system, enabling rapid similarity searches and high recall rates for its vast video content, significantly improving query throughput and operational efficiency by using Milvus' capabilities to handle and index large-scale vector data.

AT&T leverages Milvus for document search, utilizing its vector search capabilities to fetch the most relevant semantic results for customers, significantly enhancing the accuracy and efficiency of information retrieval.

HumanSignal, formerly Heartex, is a leading provider of AI data labeling solutions and is known for its open-source platform, Label Studio. It integrates Milvus into its Label Studio platform to enhance data discovery and labeling processes. Milvus's support for various indexing algorithms improves semantic search efficiency, enabling users to identify relevant data subsets swiftly. Deployed on AWS using Elastic Kubernetes Service (EKS), this integration ensures scalable and reliable data management, significantly boosting model accuracy and development speed.

VIPShop utilizes Milvus for its recommendation system, transforming product features and user behaviors into vector embeddings for fast, accurate similarity searches, outperforming traditional solutions with features like distributed deployment and multi-language SDKs.

TrendMicro adopted Milvus as a scalable, flexible vector search engine that overcame the limitations of MySQL and Faiss, enhancing APK security analysis with its advanced integration capabilities, intuitive API, and robust monitoring features, improving query performance and system scalability.

NVIDIA DRIVE is an automotive platform powering autonomous driving with advanced in-vehicle compute, simulation, and AI software. It supports the development of safer, smarter vehicles at global scale. With Milvus, NVIDIA DRIVE supports semantic, image, and video search. This helps teams retrieve relevant driving data and visual content faster.

Walmart employs Milvus across multiple use cases, with its platform team leveraging the vector database to support various internal applications, including enhancing product search capabilities by efficiently matching consumer queries with relevant product listings through advanced vector search technology.

Bosch uses Towhee and Milvus to enhance its manufacturing process by detecting defects in images, leveraging the combined power of Towhee's data processing and Milvus' vector search capabilities for improved quality control.

Fanatics Live is a digital commerce platform built around live shopping, sports collectibles, and real-time community engagement. It helps buyers and sellers discover products, join breaks, and transact around high-interest sports merchandise. With Zilliz Cloud(fully managed Milvus), Fanatics could power semantic search and recommendation across listings and live commerce content. This would help improve product discovery and buyer relevance.

Accenture is a global professional services company helping organizations transform through technology, operations, and talent development. Its platforms and services support large-scale enterprise learning, coaching, and workflow modernization. With Zilliz Cloud(fully managed Milvus), Accenture could power semantic retrieval across training content, knowledge assets, and coaching context. This would help users find relevant guidance faster.

ByteDance is a global technology company operating large-scale content and enterprise platforms across markets and languages. Its products are built to inform, educate, entertain, and support digital work at massive scale. With Milvus, ByteDance can support knowledge base retrieval across internal content and enterprise context. This helps users find relevant information faster and improves knowledge access.

Omers' Data Science/Data Engineering team is utilizing Milvus to create a semantic search solution for financial documents, harnessing Milvus' vector database capabilities to efficiently index and query complex financial data for improved insight and retrieval.

JERA is one of the world’s largest energy companies, operating across power generation, fuel, and large-scale energy infrastructure. Its business spans complex industrial assets, optimization, and the transition to lower-emission energy systems. With Milvus, JERA could power semantic retrieval across operational knowledge, engineering records, and asset data. This would help teams find relevant information faster in complex energy workflows.

Tokopedia upgraded its product search and ranking by adopting Milvus for vector similarity search, enhancing semantic understanding and efficiency over Elasticsearch, resulting in a smarter, stable, and reliable Ads service with significantly improved click-through and conversion rates.

ZipRecruiter leverages Milvus to enhance the recruitment process by embedding candidates and job opportunities in the same vector space, enabling efficient and accurate matching between job seekers and relevant positions.

PayPal utilizes Milvus for its impressive performance and scalability in handling large-scale data and AI use cases, starting with a recommender system and expanding to a multilingual customer service chatbot

Sohu uses Milvus for semantic searches, optimizing news recommendations and classification to boost user experience and content relevance.