Connected TV advertising has moved beyond simple genre and keyword targeting, but advertisers still face a basic challenge: knowing what is actually happening inside the video content surrounding their ads. Anoki AI is addressing that gap with ContextIQ, an AI-powered CTV planning platform that analyzes streaming video at the scene level. The platform has now been named AI Marketing Copilot of the Year in the 9th annual MarTech Breakthrough Awards.

Anoki AI, a video artificial intelligence company, has received the AI Marketing Copilot of the Year award for its ContextIQ platform, highlighting the growing role of multimodal AI in connected TV advertising and media planning.

ContextIQ is designed to analyze streaming video beyond conventional metadata such as genre labels, keywords and program categories. Its underlying AI technology examines visual elements, audio, dialogue, objects, emotional tone and narrative context within individual scenes.

The company's central proposition is straightforward: advertisers should be able to understand the actual content surrounding an advertisement rather than relying primarily on broad program-level classifications.

That distinction is becoming increasingly important as CTV advertising expands and marketers demand greater transparency, targeting precision and brand-safety controls across fragmented streaming environments.

According to Anoki, ContextIQ approaches video as a multimodal understanding problem. Its Copilot interface then turns that analysis into actionable media-planning recommendations.

From Genre Targeting to Scene-Level Context

Traditional CTV targeting often relies on information such as program genre, channel, audience demographics or keyword-level contextual signals.

Anoki is attempting to make the individual scene the unit of contextual analysis.

The company's AI evaluates multiple dimensions of video content, allowing advertisers to identify specific moments that align with their brand positioning or campaign objectives.

That could change how contextual CTV planning works.

Consider a sportswear brand promoting a new running shoe. A conventional contextual strategy might target sports or fitness programming. A scene-level system could potentially identify moments featuring running, outdoor activity, athletic performance or other relevant visual and narrative signals, creating a more granular connection between creative and content.

The result is closer to creative-to-context matching than conventional audience targeting.

ContextIQ Copilot Turns Briefs Into Media Plans

The Copilot component is where Anoki's video understanding becomes a media-planning workflow.

Media buyers can enter natural-language requests, campaign briefs, product information or full RFPs. The system then identifies contextually relevant scenes and produces recommendations aligned with brand objectives and suitability requirements.

Advertisers can refine the plan through a conversational interface rather than repeatedly rebuilding targeting parameters.

The platform also provides explanations for its recommendations, scene previews and information about content filtered out under brand-safety requirements.

That transparency is important.

AI-powered targeting can create a new layer of complexity if advertisers receive recommendations without understanding why a particular environment was selected. By exposing the underlying scene, Anoki is attempting to make AI recommendations more inspectable for media buyers.

Creative Becomes a Targeting Signal

One of ContextIQ's more interesting capabilities is Creative Analyzer, which analyzes an advertiser's own video creative.

The system evaluates elements such as visuals, audio, dialogue, objects, emotional tone and narrative structure. Anoki says those signals can then be used to generate CTV recommendations that correspond with the brand's creative.

This creates a two-sided contextual model.

Instead of asking only, "What content is this?" advertisers can also ask, "What does my creative communicate, and where does that meaning fit?"

That could be particularly useful for large campaigns where creative variants are designed for different audiences, products or stages of the customer journey.

It also fits a wider trend in advertising technology toward multimodal AI, where systems analyze text, images, video and audio together rather than treating each format independently.

Why Scene-Level CTV Measurement Matters

CTV has grown into a major component of the digital advertising ecosystem, but measurement and transparency remain persistent challenges.

Unlike web advertising, where marketers can often access granular page-level information, streaming environments can provide less visibility into the precise content surrounding an ad. Multiple platforms, publishers, applications and supply-side technologies can further complicate the media supply chain.

Anoki's approach attempts to address part of that problem through contextual intelligence.

The company says Copilot allows buyers to see actual scene previews before committing media dollars, understand the reasoning behind recommendations, assess brand suitability and forecast available scale.

Those capabilities could help shift contextual CTV from a broad targeting technique into a more transparent planning discipline.

Competing With the Broader CTV Technology Stack

Anoki operates in a market that includes CTV measurement companies, contextual advertising platforms, demand-side platforms and supply-side technology providers.

Companies such as DoubleVerify, Integral Ad Science and Comscore provide various forms of advertising verification, measurement, audience intelligence and media-quality analysis. Meanwhile, major advertising platforms are increasingly incorporating AI into campaign planning and optimization.

Anoki's differentiation is its focus on video understanding at the scene level.

That does not necessarily make ContextIQ a replacement for traditional verification or DSP technologies. Instead, it can sit earlier in the media-planning process, helping marketers determine which video environments are contextually appropriate before activation.

The ability to connect those recommendations with premium CTV supply and supply-side platforms could determine how valuable the technology becomes in practice.

AI Is Becoming a Planning Interface

The award also points to a broader change in marketing technology.

Natural-language interfaces are increasingly becoming the front door to complex advertising systems. Instead of navigating dozens of targeting settings, media buyers can increasingly describe the outcome they want and allow AI to translate that intent into campaign parameters.

The important question is whether the AI has enough underlying intelligence to produce reliable recommendations.

Anoki's approach is based on its video-understanding layer. The Copilot is essentially an interface sitting on top of that contextual intelligence.

That architecture resembles a broader enterprise AI pattern: specialized models and data provide domain expertise, while conversational agents make that capability accessible to users who do not need to understand the underlying technical system.

For CTV marketers, that could reduce the complexity of contextual planning while increasing the amount of evidence available before a campaign launches.

Market Landscape

CTV advertising is evolving from broad audience and program-level targeting toward more granular contextual, content and supply-path intelligence.

The market includes DSPs, SSPs, measurement companies, identity platforms and specialized contextual providers. As streaming inventory expands, marketers are increasingly looking for ways to understand not just who is watching, but what the viewer is watching at the moment an ad appears.

Anoki's scene-level approach addresses that second question.

The competitive advantage will ultimately depend on the depth and accuracy of video analysis, the breadth of inventory that can be classified and whether media buyers can activate contextual recommendations efficiently across major CTV supply partners.

Strategic Outlook

Multimodal AI could become one of the more important technologies shaping CTV advertising over the next several years.

Video contains far more information than a genre label can capture. Scene composition, dialogue, objects, sentiment, audio and narrative context can all influence whether an environment is appropriate for a particular brand.

As AI becomes capable of interpreting those signals at scale, contextual advertising can become more precise without necessarily depending on individual-level identity data.

That creates an attractive proposition in a privacy-conscious advertising environment.

For enterprise marketers, the longer-term opportunity is a CTV planning stack in which AI can translate a campaign brief into contextual environments, explain each recommendation, forecast scale and pass activation-ready signals into media-buying systems.

ContextIQ is positioning itself toward that future.

Top Insights

• Anoki's ContextIQ uses multimodal AI to analyze streaming video scene by scene, giving CTV advertisers more granular contextual intelligence than traditional genre-based targeting.
• The platform's Copilot translates natural-language briefs into contextual CTV plans, reducing manual planning while providing explanations and previews for recommended environments.
• Creative Analyzer connects an advertiser's own video content with relevant CTV scenes, creating a more direct relationship between campaign creative and contextual media placement.
• Scene-level video understanding could strengthen brand suitability and transparency as advertisers seek alternatives to increasingly fragmented audience targeting and identity-based signals.
• Anoki's award highlights a broader shift toward AI interfaces that turn complex advertising data and planning systems into conversational workflows for media buyers.

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