Build AI Video Search That Understands Content, Not Just Metadata
Zilliz Cloud powers video similarity retrieval, content understanding, and clip-level search at production scale — turning every frame into a searchable vector so your applications can find, match, and analyze video with sub-10ms precision.
Video Search Applications Powered by Zilliz Cloud
Build intelligent video search systems that go beyond metadata — finding, matching, and understanding video content at any scale with Zilliz Cloud.
Video Clip Similarity Search
Build systems that find visually similar video clips across massive libraries by comparing frame-level embeddings. Enable content teams to locate matching footage, identify reusable segments, and surface related content — in milliseconds, not hours.
Visual Product Search in Video
Let shoppers search for products they see in video content. Extract item embeddings from video frames and match them against product catalogs — turning every video into a shoppable experience with accurate, real-time results.
Video Content Moderation
Automate detection of policy-violating content across video uploads at scale. Compare frame embeddings against known violation libraries to flag harmful material before it reaches users — reducing manual review time by orders of magnitude.
Video Copyright Detection
Build copyright match systems that compare newly uploaded videos against libraries of protected content. Detect partial copies, re-edits, and derivative works by matching frame-level vectors — protecting creators without blocking legitimate uploads.
Ad and Brand Placement Detection
Enable automated detection of brand logos, products, and ad placements across broadcast and streaming video. Match visual embeddings against brand asset libraries to measure exposure, verify placements, and generate compliance reports at scale.
Video Recommendation Engine
Build recommendation systems that suggest content based on visual and semantic similarity — not just watch history. Match video embeddings to surface related clips, episodes, or creators that align with viewer preferences and engagement patterns.
Surveillance Video Retrieval
Enable fast retrieval across hours of surveillance footage by searching with reference images or video clips. Match person, vehicle, or object embeddings across multi-camera feeds — turning passive recordings into actionable intelligence.
Lecture and Training Video Search
Build search systems that let users find specific moments within educational video libraries. Extract and index frame and audio embeddings so learners can search by concept, diagram, or spoken topic — not just titles and timestamps.
Why Zilliz?
Why AI Teams Choose Zilliz Cloud for Video Search
Video search generates massive embedding volumes — every frame, clip, and object produces vectors that must be stored, indexed, and queried in real time. Zilliz Cloud handles this scale natively, delivering sub-10ms retrieval across billions of video vectors without the operational burden of self-managed infrastructure.
100K+QPS
Sustain high-throughput video queries across concurrent users
Video platforms serve millions of search and recommendation requests simultaneously. Zilliz Cloud sustains 100K+ queries per second with stable p99 latency — so your video search stays responsive during peak traffic, live events, and batch processing jobs.
10B+Vectors
Index every frame across your entire video library
A single hour of video produces thousands of frame embeddings. At platform scale, that means billions of vectors. Zilliz Cloud indexes 10B+ vectors without sharding complexity — so your video search covers every clip, every frame, every object in your catalog.
-10xCost
Scale video search without scaling your infrastructure bill
Video embedding indexes grow continuously as new content is uploaded. Zilliz Cloud's tiered storage and vector compression reduce storage costs by 10x compared to alternatives — letting you index more video content without proportionally increasing spend.
< 10msLatency
Return similar video results before users notice a delay
Users expect instant results when searching or browsing video. Zilliz Cloud retrieves the most relevant matches in under 10ms — fast enough for real-time video recommendations, live content moderation, and interactive search experiences.
Multimodal search out of the box
Combine visual embeddings with text queries, audio features, and metadata filters in a single retrieval call — enabling video search that spans modalities without building separate pipelines for each.
Automatic and elastic scaling
Automatically scales compute and storage as your video library and query volume grow — with no capacity planning, index rebuilding, or sharding required, even during traffic spikes.
Native multi-tenant architecture
Built-in tenant isolation lets you serve multiple customers, content teams, or applications on the same platform — without noisy-neighbor slowdowns or data leakage between video catalogs.
Ease of use
Go from video embedding prototype to production-ready search in minutes. Zilliz Cloud manages the infrastructure, scaling, and ops — so your team focuses on building the video experience, not maintaining databases.
Multi-cloud flexibility
Run on AWS, Azure, or GCP across 30+ regions worldwide — keeping your video search infrastructure close to your users and within your cloud strategy.
Enterprise-grade reliability and compliance
99.95% SLA with SOC 2, ISO 27001, GDPR, and HIPAA compliance — plus regional failover and BYOC support for media and entertainment workloads handling sensitive video content.
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