Power advertising technology AI from audience targeting to brand safety
Zilliz Cloud is a fully managed vector database that powers semantic audience matching, contextual targeting, and fraud detection for ad platforms â with sub-10ms latency at billion-user scale. AdTech teams use it to build cookieless lookalike audiences, match creatives to page context by meaning, and detect bot traffic that rule-based systems miss. Proven in production at SmartNews (100M+ daily vector updates, <10ms P99) and Tokopedia. SOC 2 Type II certified.
AI Capabilities for the Next Generation of Advertising Technology
Every major adtech challenge is fundamentally a similarity problem: find users like my converters, find pages matching my brand, find creatives that fit this context, find patterns that look like fraud. Zilliz Cloud gives ad platforms the infrastructure to solve these with true semantic similarity â at bid-time latency and billion-user scale.
Build Lookalike Audiences Without Third-Party Cookies
Encode first-party behavioral signals into user embeddings and find similar users via nearest-neighbor search â no cross-site tracking required. Move from declining cookie match rates to 100% first-party addressability with continuous similarity scores instead of binary segment membership.
Target by Page Meaning, Not Just Keywords
Embed page content semantically and match ad campaigns to context by meaning â distinguishing 'shooting a film' from violence, 'Apple product launch' from fruit recipes. Recapture the 76% of premium inventory that keyword blocklists incorrectly block, while improving relevance for advertisers.
Match Ad Creatives to Page Content at Impression Scale
Embed both creative assets and page content into a shared vector space using multimodal models. Find the highest-affinity creative-context pairs in real time at bid time â replacing manual tagging and pre-computed rules with automated semantic matching across millions of impressions per second.
Detect Sophisticated Ad Fraud Before It Drains Budget
Embed behavioral sessions as vectors where legitimate human patterns cluster together and bot behavior appears as outliers. Catch AI-powered bots that mimic human scrolling and click timing â the kind that rule-based thresholds miss entirely, even as they generate healthy-looking CTR and conversion metrics.
Semantic Brand Safety Beyond Keyword Blocklists
Classify page content by meaning, not individual words. Measure semantic distance from brand-unsafe concepts rather than scanning for flagged keywords â so photo shoots, basketball highlights, and film production content stop getting blocked while genuinely unsafe inventory is correctly identified.
Detect Creative Fatigue and Cannibalization Across Campaigns
Embed all active creatives and search for near-duplicates across your library. Identify creative clusters that are too visually or textually similar before they cannibalize each other's performance â shifting from reactive CTR monitoring to proactive creative rotation.
Why Zilliz?
Why ad platforms choose Zilliz Cloud
Advertising technology has three hard requirements that most infrastructure cannot meet simultaneously: sub-10ms latency to fit inside the RTB auction window, scale to handle billions of user profiles and millions of bid requests per second, and real-time index updates as user behavior and inventory change continuously throughout the day. On top of that, cookie deprecation is forcing the entire industry from exact-match identity to behavioral similarity â and keyword-based contextual targeting cannot keep pace with the semantic understanding advertisers now demand. SmartNews runs their ad matching system on Milvus with <10ms P99 latency and 100M+ daily vector updates in production. Tokopedia replaced their keyword-based ad matching with Milvus semantic search, significantly improving CTR and CVR.
100K+QPS
Handle bid-time queries at programmatic auction throughput
RTB auctions process millions of bid requests per second with an 80-120ms total window. Zilliz Cloud handles 100K+ queries per second so that semantic audience scoring, contextual matching, and fraud checks fit within the latency budget â alongside your existing bidding infrastructure, not instead of it.
<10msLatency
Return similarity results within the RTB auction window
DSPs have 10-50ms for internal processing before the auction closes. Zilliz Cloud delivers sub-10ms P99 vector search â proven in SmartNews's production ad system. Fast enough for inline audience scoring, contextual matching, and fraud detection without adding latency to the bid path.
10B+vectors
Index billions of user profiles, pages, and creative assets
Large ad platforms maintain hundreds of millions to billions of user profiles, serve ads across millions of publisher pages, and manage thousands of creative variants. Zilliz Cloud supports tens of billions of vectors in a single index â your entire user base, inventory catalog, and creative library searchable together.
-10xCost
Replace proprietary targeting tools with infrastructure you own
Proprietary contextual targeting services, brand safety vendors, and walled-garden lookalike tools charge CPM-based fees that scale with your spend. Zilliz Cloud provides the semantic matching infrastructure at a fraction of the cost â and you control the models, the data, and the methodology.
Hybrid search with metadata filtering
Combine semantic vector similarity with structured filters â match audiences filtered by geography and recency, score pages filtered by language and publisher tier, or retrieve creatives filtered by format and campaign. One query, both signals.
Real-time index updates
User behavior changes throughout the day. Zilliz Cloud supports 100M+ daily vector updates without performance degradation â keeping audience embeddings, contextual scores, and fraud models current, not stale.
Multimodal similarity search
Match ad creatives (images + text) to page content (articles + images) in a shared embedding space. CLIP-style cross-modal search enables creative-to-context matching that text-only systems cannot achieve.
Automatic and elastic scaling
Ad traffic spikes are unpredictable â prime-time surges, tentpole events, seasonal peaks. Scale compute up for high-traffic periods and back down automatically, paying only for what you use.
Multi-tenant architecture
Serve multiple advertisers, campaigns, and DSP clients from a single deployment. Fine-grained isolation ensures one advertiser's data and models never leak to another.
Enterprise-grade compliance and reliability
SOC 2 Type II certified, GDPR compliant, 99.95% SLA. BYOC deployment available for ad platforms with strict data residency and privacy requirements under GDPR, CCPA, and TCF 2.0.
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Resources
Essential reading for adtech AI teams
Explore how ad platforms use vector search for audience targeting, contextual matching, and recommendation â with production case studies and technical architecture guides.