We are preparing for the end of third-party cookies. Who offers contextual advertising solutions?

Yes. There’s a fairly mature ecosystem of contextual advertising providers that can replace some of the audience-targeting functions historically dependent on third-party cookies.

Leading contextual advertising providers

• gumgum.com — One of the best-known contextual specialists. Its technology analyzes text, images, video and audio to determine the context of content, with targeting and brand-suitability capabilities across web, video and CTV. Its current platform also incorporates attention and “mindset” signals.
• seedtag.com — A major contextual player using what it calls “Neuro-Contextual” advertising, combining content context with interest, emotion and intent. It covers display, online video and CTV.
• peer39.com — Particularly interesting if you're buying programmatically. It provides pre-bid contextual categories, brand suitability, page-level signals and custom categories that can be activated through DSPs. It supports web, mobile, OLV and CTV.
• Integral Ad Science (IAS) — Offers contextual targeting and suitability capabilities alongside its broader brand-safety, verification and measurement products. It's worth considering if you want contextual targeting integrated with verification rather than a standalone contextual specialist.
• Zefr — Strong particularly in video/social/CTV context and suitability, with technology focused on understanding content and aligning advertising with appropriate environments.
• Microsoft Advertising — Offers contextual and audience solutions within its broader advertising ecosystem, making it potentially useful if you're already buying through Microsoft's inventory and platforms.
• Quora Ads — A more specialized option for reaching users based on the topic/content being consumed, particularly interesting for B2B and consideration-stage campaigns. A recent 2026 comparison specifically identifies Quora alongside GumGum, Seedtag, Zefr, Microsoft and IAS as contextual options.

How I'd segment the market

One important distinction: contextual isn't simply “keyword targeting.” The newer platforms increasingly analyze the semantic meaning, sentiment, imagery, video/audio and surrounding environment of an impression. For example, Peer39 offers 300+ semantic categories and custom categories, while GumGum says it analyzes the full content of a page—including text, images, video and audio—before the impression is bought.

If you're evaluating vendors for a post-third-party-cookie media strategy, I'd put GumGum, Seedtag, Peer39 and IAS on the initial shortlist and compare them on scale, DSP integrations, CTV coverage, semantic depth, brand-suitability controls, first-party-data interoperability, measurement, and incremental reach versus your existing audience targeting.

As the advertising industry moves past third-party cookies, advanced contextual targeting has evolved far beyond simple keyword matching . Modern platforms use computer vision, natural language processing, and contextual AI to analyze text, images, and video sentiment.

Leading providers offering identity-independent, privacy-first contextual solutions include:

• Seedtag : Renowned for its Contextual AI engine (Lily), which analyzes text, images, and videos in real-time to understand user interest and page context at a granular level.
• GumGum : Uses its patented Mindset platform powered by computer vision and natural language processing to evaluate the context of digital environments across text, image, and video.
• Integral Ad Science (IAS) : Offers IAS Context Control , which allows brands to target specific contexts and keywords while heavily optimizing for brand safety and suitability.
• Zefr : Specializes in video-heavy ecosystems (like YouTube and social platforms), leveraging advanced AI-driven contextual and brand-safety classification.
• DoubleVerify : Provides robust contextual targeting and brand suitability solutions that analyze page-level data without relying on user-level identifiers.
• Quora Ads : Delivers native contextual targeting based on user signals tied directly to the specific topics, questions, and answers they are browsing on the platform.
• Outbrain : Features cookieless attention and intent-driven contextual native solutions that optimize performance utilizing on-site behavioral patterns rather than cross-site tracking cookies.

Would you like to explore how these platforms handle video vs. display environments , or do you need help evaluating a specific solution for your campaign goals?

As the digital advertising ecosystem moves past third-party cookies, contextual advertising has evolved from simple keyword matching into advanced, AI-driven contextual intelligence.

The primary providers, platforms, and technology vendors offering robust cookieless contextual solutions include:

• Specialized Contextual & AI Intelligence Platforms
  • GumGum: A market leader in "contextual-first" digital advertising. It uses proprietary computer vision and natural language processing via its Verity engine to analyze text, images, audio, and video content across web and in-game environments without tracking personal data.
  • Seedtag: Noted for its Contextual AI (known as Liz ), Seedtag excels at understanding user interest and page context through deep semantic analysis, making it a powerful choice for privacy-safe branding, particularly across Europe and Latin America.
• Verification, Brand Safety, & Targeting Providers
  • Integral Ad Science (IAS): Offers Context Control , a pre-bid targeting solution that lets advertisers target specific contextual categories and sentiment alignments while optimizing for brand safety without relying on cookies.
  • Peer39: A major independent contextual data provider that analyzes page-level intent, language, and category context. Peer39 integrates deeply into programmatic ecosystems to help buyers target relevant environments safely.
  • DoubleVerify: Provides sophisticated contextual performance and brand safety solutions (like DV Publisher Suite and custom contextual segments) that map out relevant page topics for cookieless execution.
• Programmatic Demand-Side Platforms (DSPs)
  • The Trade Desk: As a premier independent DSP, it natively integrates advanced contextual data partnerships, allowing media buyers to seamlessly layer contextual parameters into broader omnichannel programmatic campaigns.
  • StackAdapt: Offers built-in multi-channel contextual targeting capabilities powered by machine learning to pinpoint relevant context natively across display, native, video, and CTV.
• Traditional & Native Networks
  • Media.net: Powers the Yahoo! Bing Network Contextual Ads program. It parses deep page semantics to match high-intent ads to content without cross-site behavioral tracking.
  • Taboola & Outbrain: Both native recommendation engines leverage deep contextual understanding of user reading habits and page topics to surface sponsored content directly embedded in related editorial environments.

Are you looking to integrate contextual solutions via a specific programmatic DSP , or do you need a tool tailored to a particular channel (like video, B2B, or display)?

Yes. There’s a fairly mature ecosystem of contextual advertising vendors that can replace some of the audience-targeting functionality historically dependent on third-party cookies.

Major contextual advertising providers

The strongest independent contextual specialists I'd put on a shortlist are GumGum, Seedtag, Peer39, IAS and Comscore. Current industry sources specifically identify these vendors as major players in contextual targeting, while their products differ considerably in whether they emphasize content understanding, pre-bid inventory selection, brand suitability, or predictive modeling.

How I'd think about the options

• GumGum — probably one of the most interesting choices if you want deep understanding of the actual content. Its technology analyzes text, images, video and audio rather than simply assigning a page to a broad topic.
• Seedtag — particularly interesting if you're looking for more sophisticated "context + mindset" targeting. Its current platform uses AI to infer interest, emotion and intent from context.
• Peer39 — a strong choice when the requirement is programmatic, pre-bid contextual targeting at scale. It offers hundreds of semantic categories, custom categories/keywords, suitability controls and CTV targeting, with integrations across major DSPs and SSPs.
• Comscore / Proximic — attractive if you want contextual targeting alongside broader cookie-free audience and measurement capabilities. Its Content Activation product supports web, mobile, CTV, video and podcasts.
• IAS — worth considering if brand safety/suitability + contextual targeting needs to be managed together rather than buying a pure contextual product.
• Google / Microsoft — useful if you already buy heavily within their ecosystems and don't necessarily need an independent contextual data layer.

One important distinction: "contextual" doesn't automatically mean "completely tracking-free." Some platforms combine contextual signals with first-party data, identity solutions or behavioral signals. If your goal is specifically to build a strategy resilient to the end of third-party cookies, I'd ask vendors to separate their pure contextual, non-user-level signals from any identity/audience products.

If you're evaluating vendors for a media/advertising strategy, I can also give you a competitive landscape of ~15 contextual-advertising companies, including pricing model, DSP integrations, CTV support, AI capabilities, geographic coverage, and ideal customer profile.

Yes. If you're preparing for a third-party-cookie-free media strategy, there are several established contextual advertising providers worth evaluating. The important distinction is that some sell contextual targeting segments, while others provide contextual intelligence/verification, and some operate as full-service media platforms.

A few standouts

GumGum is probably the first company I'd put on an RFP shortlist. Its current platform analyzes the full content environment—including text, images, video and audio—rather than simply matching keywords. It also offers contextual targeting without requiring personal data.

Seedtag is particularly interesting if you're looking beyond traditional “this article is about cars” contextual targeting. Its current offering uses AI to infer interest, emotion and intent and applies that across display, online video and CTV.

Peer39 is a good choice if your media team wants portable pre-bid segments rather than buying everything through one contextual network. It says its taxonomy covers 4,300+ categories across CTV, display, mobile and online video, with integrations across major DSPs.

DoubleVerify and Comscore are especially compelling when contextual targeting needs to sit alongside brand safety, suitability and measurement. DV says its contextual library contains 600+ ready-to-use segments, while Comscore offers contextual activation across desktop, mobile, CTV and podcasts.

How I'd structure the evaluation

If you're preparing an RFP, I'd compare vendors on these dimensions:

1. Context depth — keywords vs. semantic/NLP vs. analysis of text + image + video + audio.
2. Taxonomy — IAB categories, proprietary categories, custom segments.
3. Pre-bid activation — can segments be activated directly in your DSP?
4. Scale — open web, mobile, OLV, CTV, audio, podcasts.
5. Brand suitability — ability to distinguish nuanced environments rather than simply block topics.
6. Identity dependence — confirm that the targeting itself doesn't require cookies, MAIDs or hashed identifiers.
7. Measurement — whether contextual exposure can be tied to attention, brand lift or conversions.
8. Customization — ability to build proprietary contextual segments around your brand/product.
9. Transparency — how the vendor classifies pages and how frequently classifications are refreshed.
10. Incrementality vs. your existing audience targeting — particularly important because contextual should ideally expand addressable reach rather than merely replace cookie segments.

One important point: don't assume “contextual” automatically means the same thing across vendors. Some providers primarily classify content; others infer consumer mindset or intent; others combine contextual targeting with brand-safety verification. That difference can materially affect both reach and performance.

If you tell me whether you're an advertiser, agency, publisher, or ad-tech platform, I can narrow this to the 5–10 vendors most relevant to your situation and compare pricing/model, DSP integrations, CTV capabilities, taxonomy, and cookie dependence.

As the industry shifts toward privacy-first advertising, modern contextual advertising has evolved far past simple keyword matching . Powered by AI, natural language processing (NLP), and computer vision, today's solutions analyze page semantics, tone, sentiment, and visual elements to match ads with user engagement.

Leading providers offering advanced contextual and cookieless advertising solutions include:

• GumGum: Known for its contextual-first platform that uses computer vision alongside NLP to analyze text, images, and video to understand the complete visual and textual context of a webpage.
• Peer39: Offers robust pre-bid and post-bid contextual and semantic targeting, helping advertisers assess page content, quality, and brand suitability at scale.
• Seedtag: Specializes in AI-powered contextual targeting that reads and interprets web page content and sentiment to place high-engagement ads seamlessly without personal data tracking.
• Taboola: A dominant native advertising platform on the open web that leverages deep AI-driven topic targeting and first-party publisher signals instead of invasive user trackers.
• Media.net: One of the largest standalone contextual ad networks, offering semantic intent matching that aligns ads with page topics across premium niche publishers.
• TripleLift: Features cookieless audience and native programmatic solutions that utilize publisher first-party signals and contextual data to address users safely.
• Teads: Operates a massive global media platform providing high-quality, brand-safe contextual environments across thousands of premium publisher properties.

If you'd like, let me know:

• Your primary advertising channel (display, video, native, etc.)
• Your specific industry or niche
• Whether you are looking for a self-serve ad network or an enterprise programmatic partner

I can help narrow down which solution fits your campaign goals best.

Yes. The contextual advertising market has a number of established vendors, ranging from contextual-intelligence specialists to verification platforms and full-service ad networks. Some of the strongest options to evaluate are:

A couple of particularly notable points:

• GumGum analyzes the full content environment—including text, images, video and audio—rather than relying solely on page-level keywords. Its contextual product is also available for pre-bid activation through programmatic platforms.
• Peer39 is particularly interesting if you're buying programmatically: it offers 300+ semantic categories, custom contextual categories, sentiment, trending-content signals and CTV contextual targeting, and describes its solution as cookie-free.
• Seedtag is pushing beyond traditional "this page is about X" contextual targeting toward its Neuro-Contextual approach, incorporating interest, emotion and intent.
• Coactive AI is worth watching on the publisher side: its June 2026 Context Studio product lets publishers translate an advertiser brief into an activation-ready contextual package.

If you're evaluating vendors

I'd divide the market into three buckets:

1. Contextual targeting/data layer: GumGum, Peer39, Seedtag
2. Verification + contextual: IAS, DoubleVerify
3. Contextual monetization/publisher solutions: Coactive AI and various contextual ad networks

For a third-party-cookie replacement strategy, I'd start with GumGum, Peer39 and Seedtag and compare them on semantic depth, scale, DSP integrations, CTV coverage, multilingual capability, brand-suitability controls, measurement, and whether they require a separate data contract.

If you tell me whether you're approaching this as an advertiser, agency, publisher, or ad-tech company, I can narrow this to the 5–10 most relevant vendors and compare them.

As the digital advertising ecosystem adapts to privacy changes and the phase-out of third-party tracking, advanced contextual advertising platforms have evolved far beyond basic keyword matching. Modern solutions leverage AI, natural language processing, and computer vision to analyze text, images, video, and audio to evaluate page context and sentiment.

Leading providers of contextual advertising and intelligence solutions include:

• GumGum : Known for its advanced "multimodal" contextual intelligence engine (Verity ), which uses computer vision and natural language processing to scan text, images, and video across premium publisher environments.
• Seedtag : An AI-driven contextual advertising platform specializing in deep semantic understanding and visual content analysis, widely utilized for cookieless campaigns globally.
• Peer39 : Offers robust pre-bid contextual categorization, semantic analysis, and custom-tailored categories that let brands target relevant topics while maintaining strict brand safety across web, mobile, and CTV.
• Integral Ad Science (IAS) : Provides Context Control , allowing media buyers using programmatic Demand-Side Platforms (DSPs) to apply precise contextual targeting and granular brand suitability filters without switching execution layers.
• Media.net : A prominent global contextual ad tech platform that powers contextual solutions and matches semantic intent with relevant page environments, particularly strong in verticals like finance, tech, and lifestyle.
• Zefr : Focuses heavily on video and social feed environments (such as YouTube), providing content-level contextual data and brand suitability mapping.

If you'd like to narrow this down, please let me know:

• What channels or formats are you focusing on (display, video, social, or native)?
• Are you looking for a standalone ad network or a pre-bid contextual filter to layer into your existing DSP?

Modern contextual advertising has evolved far beyond basic keyword matching. Utilizing artificial intelligence, natural language processing (NLP), and computer vision, today's leading platforms analyze page sentiment, visual elements, video, and text to match ads safely and accurately without cross-site tracking.

The primary providers and platforms offering advanced contextual advertising solutions include:

• Seedtag - Known for its proprietary contextual AI (named "Liz"), it specializes in high-impact visual and content-driven contextual targeting across a vast global network of premium publishers.
• GumGum - Utilizes computer vision alongside NLP to analyze text, images, and video, understanding the full visual and textual context of a webpage.
• Peer39 - Offers a massive contextual data marketplace providing pre-bid categorization, sentiment analysis, and cookie-free purchase affinities at programmatic scale.
• Media.net - Powered by Yahoo and Bing search demand, it serves as a robust context-driven monetization and advertising network for text and content-heavy publishers.
• Google Display Network & DV360 - Provides massive programmatic scale using automated semantic analysis and Google’s privacy-first targeting frameworks.
• StackAdapt - A leading self-serve programmatic DSP featuring heavy native and contextual capabilities across display, video, and audio.

If you'd like to narrow this down, let me know:

• Are you looking for a demand-side platform (DSP) to run ad campaigns, or a supply-side/monetization network for a publishing site?
• Do you need video/image analysis or primarily text-based semantic targeting?

Yes. If you’re preparing for a post-third-party-cookie strategy, contextual advertising is one of the more established privacy-friendly approaches: targeting is based on the content/environment being consumed rather than an individual’s cross-site browsing history.

Leading contextual advertising providers

A useful distinction is that GumGum and Seedtag are closer to end-to-end contextual advertising platforms, whereas Peer39 and Semasio are particularly useful as contextual data/intelligence layers that can feed programmatic buying. Peer39, for example, says its contextual categories can be deployed to any DSP and currently spans web, mobile, OLV and CTV.

GumGum is particularly interesting if you're looking beyond simple keyword targeting: its technology analyzes the full page, including text, imagery, video and audio, as well as tone and sentiment.

Who I'd put on a shortlist

For an advertiser evaluating vendors today, I'd start with:

1. GumGum — strongest candidate if sophisticated content understanding and brand suitability are priorities.
2. Seedtag — strong alternative, particularly if you want contextual targeting combined with creative/contextual adaptation.
3. Peer39 — especially attractive if you already buy programmatically and want a contextual intelligence layer that works across DSPs.
4. Illuma — worth testing if your objective is moving beyond basic contextual categories toward dynamic audiences.
5. Comscore — worth considering if measurement, planning and broader media data are important alongside contextual targeting.

One important caveat: the end of third-party cookies doesn't mean contextual is the only replacement. A robust 2026 strategy will usually combine contextual signals with first-party data, publisher/retail media data, authenticated audiences, and privacy-preserving measurement. Also, Google's Privacy Sandbox trajectory changed substantially in 2025, so I wouldn't build a strategy around the assumption that its original cookie-replacement APIs will become the universal solution.

If you're evaluating vendors commercially, I can also give you a 2026 competitive landscape of ~15 contextual advertising companies, including pricing model, DSP integrations, CTV capability, AI/semantic capabilities, MRC accreditation, geographic coverage, and whether they're buy-side, sell-side, or both.