Editorial Review by TopAdNetworks
RTB House has built one of the most technically distinctive positions in performance advertising by making a complete architectural commitment: its entire ad buying engine runs on Deep Learning, not just as a feature layer on top of conventional optimization logic, but as the foundational infrastructure. This means every bid, every audience model, and every creative decision is driven by neural networks trained on behavioral signals rather than rule-based heuristics. The company completed this transition by 2018 and has since compounded that advantage across 90+ markets.
What makes RTB House relevant in 2026 is not just its technology heritage but its positioning for the cookieless era. The platform was built private-by-design from the start, relying on first-party behavioral signals rather than third-party cookie data.
As browser restrictions and regulatory pressure have continued to erode the reliability of cross-domain tracking, RTB House has found itself structurally well-positioned: it does not need to rebuild around consent, because it was never built on data that required it.
The launch of rtb.com in March 2026 marks a powerful strategic pivot. RTB House has historically operated as a fully managed service for large enterprise advertisers. The new self-service platform opens the same Deep Learning infrastructure to small and medium-sized ecommerce brands, with no minimum budgets and no long-term contracts, and integrates with Shopify to automatically generate personalized, dynamic product ads. This expansion targets a segment that advanced programmatic advertising has largely priced out, positioning RTB House to expand its addressable market substantially.
With approximately $474 million in 2024 revenue, more than 1,400 employees globally, and zero outside funding, RTB House is arguably the most financially independent scaled AdTech company in Europe.
Its continued investment in AI capabilities, including the ContentGPT generative AI layer introduced in late 2023, and in subsidiaries such as the Adlook brand-focused buying platform and the PrimeAudience audience data solution, shows a company building a full-funnel ecosystem rather than a single-product retargeter.
Company Overview
RTB House was founded in 2012 in Warsaw, Poland, by Robert Dyczkowski, Daniel Surmacz, Bartlomiej Romanski, and Pawel Chodaczek, incorporating formally as a joint-stock company in May 2013.
The company grew organically without external venture capital, reaching $474.2 million in annual revenue by 2024, with an estimated $417.5 million run rate referenced in 2026 data from multiple commercial intelligence sources.
Headcount stands at approximately 1,400 employees across more than 30 offices on six continents, including key hubs in New York, London, Tokyo, Singapore, Sao Paulo, Dubai, and Warsaw.
The company’s CEO is Robert Dyczkowski, with Daniel Surmacz serving as COO and Michael Lamb as Chief Commercial Officer. RTB House operates as a standalone parent company with several subsidiaries: Adlook (a brand-focused programmatic buying platform), PrimeAudience (a data and audience solutions product), NapoleonCat (a social media management tool, acquired in 2021), and WhitePress (a content distribution platform). This group structure allows RTB House to serve both performance and brand objectives across the purchase funnel.
The company is recognized as a Great Place to Work globally and has served more than 3,000 active campaigns across its client base, which spans ecommerce, travel, gaming, finance, and other performance-focused verticals. RTB House completed the industry’s first full migration to Deep Learning for all campaign types in 2018 and has continued to layer generative AI capabilities on top of that infrastructure, most notably with the ContentGPT announcement in November 2023.
How The Platform Works
RTB House operates as a demand-side platform (DSP) that connects to supply-side platforms (SSPs) and ad exchanges through real-time bidding auctions. When a user visits a website with RTB House pixel tracking in place, a bid request is sent to RTB House’s buying engine, which evaluates the user’s behavioral profile and predicted purchase intent within milliseconds. If the user matches a target audience for an active campaign, RTB House submits a bid. If the bid wins, a personalized ad is served, dynamically generated from the advertiser’s product catalog and tailored to the individual user’s browsing history and interests.
The core differentiator is that every step in this process, including audience scoring, bid price calculation, creative selection, and frequency management, is handled by Deep Learning models rather than rules or simpler machine learning approaches. This allows the engine to process more complex behavioral signals and optimize for delayed conversion events that simpler attribution systems would miss entirely.
For the rtb.com self-service product, the same algorithmic infrastructure is made accessible to smaller advertisers through an automated setup process that removes the need for dedicated campaign management.
Advertiser Onboarding
Managed service (enterprise) – dedicated RTB House account teams handle onboarding and include:
- Pixel installation on the advertiser’s website for first-party behavioral data capture
- Product catalog feed integration for dynamic creative generation
- Campaign goal setting: conversion, acquisition, engagement, or demand generation
- Audience strategy definition and Deep Learning model initialization
- Campaign launch and ongoing performance management by RTB House’s team
Self-service (rtb.com, launched March 2026):
- Store integration via the Shopify Connector App in a few clicks
- Product catalog sync: ads are auto-generated from the existing catalog
- Budget and campaign objective setup through an intuitive dashboard
- Campaign goes live with no minimum budget and no long-term contract
Ad Formats And Placement
- Dynamic display banners: personalized product ads auto-generated from the advertiser’s catalog
- Rich media and interactive banners: Social Banners and Snippet Ads formats
- Video: in-stream and out-stream video for branding and performance campaigns
- Mobile: in-app and mobile web display formats
- Native: content-matched placements across the open web
- Context AI placements: inventory selected based on real-time contextual signals using ContentGPT
Targeting And Optimization
- Behavioral retargeting: users segmented by on-site actions, including product views, cart additions, and purchase history
- Prospecting and acquisition: Deep Learning models identify new users with similar behavioral profiles to existing converters
- Contextual targeting via Context AI: page-level content analysis using GPT and LLM technology for cookieless targeting
- Audience data targeting via PrimeAudience: third-party audience segments enhanced with ContentGPT-powered segmentation
- Geo-targeting: regional and country-level campaign segmentation across 90+ markets
- Frequency capping and budget pacing: automated controls to prevent overexposure and manage spend efficiency
- Creative optimization: Deep Learning selects and rotates creatives dynamically for each impression
Key Differentiators
RTB House’s competitive position rests on a set of deeply integrated technological and strategic advantages that distinguish it from conventional DSPs and retargeting providers. The following differentiators define what the platform does differently and why they matter for advertisers in 2026.
1. 100% Deep Learning Buying Engine
RTB House is the only global DSP to have fully migrated its entire ad buying infrastructure to Deep Learning, completing this transition in 2018. Unlike platforms that apply AI as an optimization layer on top of rules-based bidding, RTB House’s engine uses neural networks at every decision point: audience scoring, bid valuation, creative matching, and campaign pacing. This enables the system to identify conversion patterns across thousands of behavioral variables simultaneously, outperforming simpler models on delayed and complex conversion events.
2. First-Party, Cookie-Free Architecture
RTB House was designed from the outset around first-party behavioral signals, captured through its own pixel and product feed integrations. The platform does not depend on third-party cookie data for audience identification or campaign targeting. As cross-domain tracking has become increasingly restricted through browser policy changes and GDPR enforcement, RTB House’s infrastructure has remained unaffected. The ContentGPT generative AI layer, introduced in November 2023, extends this by enabling deep contextual understanding of page content as an alternative signal for audience classification.
3. Full-Funnel Coverage from Retargeting to Prospecting
While RTB House is best known for retargeting, its product range spans the entire purchase funnel. Retargeting campaigns re-engage users who have already visited an advertiser’s site. Acquisition campaigns use Deep Learning models trained on existing converter profiles to identify and reach new customers. Branding campaigns, supported by video and rich media formats, build awareness upstream. This full-funnel capability allows clients to run all performance objectives through a single partner and measure cross-funnel incrementality from one platform.
4. rtb.com Self-Service Platform for SMEs (launched March 2026)
The March 2026 launch of rtb.com represents a significant democratization of enterprise-grade programmatic technology. The platform gives small and medium-sized ecommerce brands access to the same Deep Learning infrastructure used by RTB House’s largest enterprise clients, with no minimum budget requirements, no long-term contracts, and a Shopify-native integration that automates the entire setup process. Dynamic product ads are generated automatically from the product catalog, removing the creative production barrier that has historically kept smaller advertisers out of advanced display advertising.
Ideal Use Cases
RTB House is best suited for performance-focused advertisers who need high-precision retargeting or acquisition campaigns and want to operate with a technology partner rather than managing complex DSP interfaces themselves.
- Ecommerce retargeting: re-engaging users who browsed products or abandoned carts, using dynamic product ads auto-generated from the catalog
- New customer acquisition: scaling beyond retargeting using Deep Learning models trained on existing buyer profiles to prospect into new audiences
- Cross-market campaign management: brands operating simultaneously across EMEA, APAC, and the Americas who need a single partner with local market expertise and inventory access in 90+ markets
- SME ecommerce advertising: smaller brands accessing enterprise-grade programmatic technology through the rtb.com self-service platform without minimum budget commitments
- Travel and ticketing: high-intent retargeting for travel brands where purchase cycles involve multiple sessions and comparison shopping
- Gaming and app install campaigns: driving engagement and re-engagement for gaming brands through mobile and display inventory
Target Clients
Advertisers
RTB House’s primary client base consists of performance-oriented advertisers in ecommerce, travel, gaming, and finance, ranging from global enterprise brands managing multi-market campaigns to small and medium-sized online retailers accessing the platform through the rtb.com self-service product. Enterprise clients typically work with RTB House through a fully managed service model, where dedicated account teams handle campaign strategy, creative production, optimization, and reporting. Advertiser clients include both direct brands and agency buyers managing campaigns on behalf of multiple clients.
Publishers
RTB House operates as a buyer in programmatic auctions, accessing premium and mid-tail publisher inventory through integrations with major SSPs and ad exchanges. Publishers benefit indirectly from RTB House’s presence in the ecosystem through increased demand competition for their inventory.