Ad Tech & Measurement
Use Cases
Where ad tech plugs in.
What measurement unlocks.
Ad tech and measurement companies are being asked to deliver content-level understanding of video at programmatic scale, and the engines most of the industry runs on were built for web pages and keywords. Building moment-level multimodal classification in-house means standing up model infrastructure, evaluation pipelines, and catalog-scale processing that never stops evolving. The Coactive Multimodal AI Platform is that layer, built once and built to last as models change, so platforms, data providers, and measurement companies can ship deeper products instead of maintaining deeper pipelines.
Power Contextual & Brand Safety Products
Contextual and verification engines were built for an era of pages, keywords, and category taxonomies. Premium video at the moment level, across full catalogs, with classification logic tailored to each advertiser, is a different scale of problem. Coactive provides the multimodal engine underneath: Dynamic Tags let every client define custom taxonomies in natural language rather than waiting on model retraining, and the platform's ground-truth and evaluation loop gives accredited vendors the precision and defensibility their products are sold on.
Extend Title-Level Metadata to the Moment Level
Title-level descriptors tell buyers what a show is. They cannot tell buyers what happens inside it, and the value in contextual advertising, discovery, and analytics is moving inside the content. Data and metadata providers run their established taxonomies and editorial standards through Coactive to generate moment-level metadata across entire partner catalogs, processing thousands of hours per hour, with their own validation workflows as the ground-truth layer. Their taxonomy and their standards, operating at a depth and scale no editorial process can reach alone.
Enable Contextual Curation & Marketplaces
Curation products and contextual marketplaces need consistent, validated, publisher-permissioned moment-level signal to package into deals, and the cost of producing that signal has been the bottleneck holding adoption back across the ecosystem. Coactive generates the signal upstream with platform economics, so sell-side platforms and ad servers can package, price, and transact inventory that was previously untaggable, without asking every publisher to fund a bespoke classification pipeline.
Before an impression is ever bought, demand platforms decide what to bid on with content signals that top out at genre, rating, and production quality. Coactive enables publishers to generate moment-level contextual signal from their own catalogs and opt in to exposing it to the demand platforms and marketplaces they choose. For DSPs, that means targeting and planning decisions informed by what is actually inside the content, sourced with publisher consent rather than scraped or inferred around them. The signal gets deeper, the publisher stays in control of their data, and the demand platform inherits a planning vocabulary no standard taxonomy provides.
After the impression, measurement providers work with delivery and outcome data but lack granular visibility into context: the programming the ad ran adjacent to, and the creative itself. Coactive's moment-level metadata describes both in multi-dimensional detail. Joined with a provider's other data sources and capabilities, it powers the products clients are already asking their measurement partners to deliver: explainability for why placements performed, creative effectiveness grounded in what creatives actually contain, and sponsorship and brand visibility measurement at the moment level.
The move to
contextual advertising
Why content intelligence is becoming core infrastructure, and how it closes the gap between advertiser intent and publisher supply. Covers the three structural forces, the revenue case for contextual, and real-world use cases across the ecosystem.
