Kontext secures $10M to scale AI-powered advertising in GenAI apps – PPC Land
Startup claims 66% revenue increase through contextual ad technology targeting AI chatbots.
Kontext, a startup developing artificial intelligence-powered advertising infrastructure for generative AI applications, announced on April 1, 2025, that it has raised $10 million in seed funding to expand its contextual advertising platform.
The 13-person company, founded in 2023, specializes in creating advertisements dynamically using large language models tailored to individual user sessions within AI chatbots and conversational interfaces. According to company documents, Kontext processes tens of millions of daily ad impressions and serves major consumer brands including Amazon, Uber, and Canva.
M13 led the funding round, with participation from Torch Capital, Credo Ventures, and Parable VC. Kontext indicated the capital will support team expansion, infrastructure development, and demand subsidization as the platform scales operations.
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Kontext’s core technology generates advertisements in real-time within AI conversational interfaces rather than displaying static banner advertisements. According to the company’s pitch deck, “We create every ad in real-time, tailored to user’s particular intent and context, in UX that is native to chatbots.”
The platform operates by analyzing user queries and conversation context through the same large language models powering the host application. This analysis enables the system to generate contextually relevant advertising content that appears as branded links beneath chatbot responses.
Current publisher partners include DeepAI, Media Search, Pixel Chat, and Spicy Chat. The company reports average revenue per user improvements from $0.24 to $0.40 among GenAI applications implementing its advertising layer – representing a 66% increase through ad-supported monetization.
Kontext conducted a pilot campaign with casual game developer Nimblebit for the mobile game Tiny Tower. According to company data, the campaign achieved a 1.58% click-through rate and cost-per-install below $2. The company reports its campaign outperformed concurrent Facebook campaigns by 24%, with Kontext achieving $2.50 CPM compared to Facebook’s $7.35 CPM.
The advertising platform operates on a revenue-sharing model, taking 25-30% from actual filled advertising demand, according to the business model documentation. The company also charges success fees of 20-30% of lifetime value for premium publisher upsells.
The startup positions itself within what it characterizes as a platform transition from mobile to AI-powered consumer applications. According to Kontext’s analysis, “There’s a new category of mass-market consumer products powered by AI” similar to previous transitions from web to mobile platforms in the 2000s and 2010s.
Traditional advertising infrastructure companies including AdSense, TheTradeDesk, and AppLovin developed around web and mobile platforms, creating what Kontext describes as a missing infrastructure layer for AI-powered applications. The company estimates a $500 million revenue potential within GenAI text publishers as its initial market segment.
The implementation differs significantly from traditional display advertising systems. Instead of pre-created creative assets, Kontext’s platform must generate advertisement copy dynamically based on real-time conversation analysis. This approach requires substantial computational resources and sophisticated natural language processing capabilities.
The company identified several technical advantages supporting its approach. Text-based advertisements represent the most cost-efficient format given current AI infrastructure limitations. GenAI applications already operate with high marginal costs due to inference requirements, making advertising-supported monetization particularly attractive for free user tiers.
According to the company’s documentation, “Due to high marginal costs, GenAI products benefit greatly from ad-based monetization of free users.” This economic reality has driven adoption among publishers seeking revenue diversification beyond subscription-only models.
Kontext faces competition from both startups and established advertising technology companies. Identified competitors include OpenAds.AI, Abotify, Prompt Ads, and Koah among smaller companies with limited funding and traction. Large technology companies including Google, Meta, Microsoft, and TheTradeDesk represent potential competitive threats, though Kontext argues these companies lack real-time ad product capabilities for third-party advertisements.
The company contends that incumbents face significant challenges adapting existing technology infrastructure to support real-time advertisement generation. Traditional advertising systems require complete technical stack modifications to accommodate real-time creative generation while addressing brand safety concerns around AI-generated content.
Kontext’s seven-person team consists entirely of individuals who previously co-founded startups. The team has produced over 400 citations across AI research papers, according to company documentation. Leadership includes Jan Matas, co-founder and CTO at Deepnote, which raised over $20 million from Index and Accel, and Andrej Kiska, co-founder of Credo Ventures and early investor in UiPath, Eleven Labs, and Productboard.
The technical expertise spans artificial intelligence research, infrastructure development, and advertising technology. This background positions the company to address both the AI-specific requirements of contextual content analysis and the scalability demands of advertising infrastructure.
According to Kontext’s testing with publishers, the advertising platform increased Average Revenue Per User among GenAI applications. A comparison study showed users in the default group (10,101 users) generating $0.24 revenue per user, while the ad-supported group (91,088 users) achieved $0.40 revenue per user.
The ad-supported group also demonstrated higher conversion rates to paid subscriptions (2.13% versus 1.46%) and increased total subscriber revenue ($30,502.50 versus $2,389.30), suggesting that advertising implementation enhances rather than cannibalizes subscription conversions.
These performance metrics indicate that contextual advertising within AI applications provides monetization benefits without negatively impacting user experience or subscription upgrade rates.
The funding announcement occurs amid broader industry recognition that advertising models will expand into AI-powered platforms. Netflix, which previously stated it would never include advertisements, launched an ad-supported tier in 2022, demonstrating how economic pressures drive advertising adoption across consumer platforms.
Google’s expansion of AdSense into AI chatbot conversations signals major technology companies recognizing the commercial potential of advertising within conversational AI interfaces. Recent developments in conversational advertising formats demonstrate growing market acceptance of AI-powered advertising integration.
The timing aligns with broader industry trends toward AI-driven advertising automation, where 86% of buyers currently use or plan to implement generative AI for advertisement creation. New AI advertising models where agents could replace human attention suggest fundamental shifts in how digital advertising operates.
Kontext’s system requires integration with existing AI application infrastructure while maintaining response time performance standards. The platform must analyze conversational context, match appropriate advertisers, generate contextually relevant creative content, and deliver results within the response time constraints of interactive chatbot experiences.
The technical challenges include ensuring brand safety for AI-generated advertising content, maintaining relevance across diverse conversation topics, and scaling computational resources to support real-time advertisement generation across millions of daily user interactions.
The company’s infrastructure must also support multiple targeting criteria, campaign optimization algorithms, and performance measurement systems while operating within the technical constraints of third-party AI applications.
Kontext projects significant market expansion as AI-powered consumer applications achieve mainstream adoption. The company estimates that major platforms including ChatGPT, Character.ai, and Perplexity represent opportunities for advertising infrastructure similar to previous platform transitions.
Historical advertising infrastructure acquisitions provide context for potential market size. AdSense achieved a $300 billion valuation, TheTradeDesk reached $70 billion, and AppLovin attained $110 billion market capitalizations during their respective platform cycles.
The $140 billion open web advertising market provides additional context for Kontext’s positioning as AI applications increasingly compete for user attention and engagement across digital platforms.
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Real-time ad generation: The process of creating advertisement content dynamically during user interactions rather than using pre-created static materials. This technology represents a fundamental shift from traditional advertising models where creative assets are produced weeks or months in advance. Kontext’s implementation analyzes conversational context through large language models to generate contextually appropriate advertising copy within milliseconds of user queries. The approach requires sophisticated natural language processing capabilities and substantial computational resources but enables unprecedented personalization and relevance in advertising delivery.
Contextual advertising: A targeting method that places advertisements based on the content and context surrounding the ad placement rather than user behavioral data or tracking identifiers. In Kontext’s implementation, contextual signals derive from real-time conversation analysis, understanding user intent and topic relevance without requiring personal data collection. This approach addresses privacy concerns while maintaining advertising effectiveness, particularly important as third-party cookie deprecation accelerates across the industry.
Large language models (LLMs): Advanced artificial intelligence systems trained on vast datasets to understand and generate human-like text. Kontext leverages the same LLMs powering host AI applications to analyze conversation context and generate appropriate advertising content. These models enable the platform to understand nuanced conversational intent and create advertising copy that feels natural within the conversational flow, representing a significant technical advancement over keyword-based advertising systems.
GenAI applications: Software platforms powered by generative artificial intelligence that create content, engage in conversations, or assist users with various tasks. These applications include chatbots like ChatGPT, Character.ai, and Perplexity, representing a new category of consumer products with unique monetization challenges. GenAI applications typically operate with high inference costs, making advertising-supported revenue models particularly attractive for sustaining free user access while generating revenue from non-paying users.
Revenue per user (RPU): A key performance metric measuring the average revenue generated from each user over a specific period. Kontext’s impact on publisher RPU demonstrates the effectiveness of its advertising integration, with documented increases from $0.24 to $0.40 representing 66% improvement. This metric provides clear evidence of advertising implementation success and helps publishers evaluate the financial impact of integrating advertising layers into their AI applications.
Cost per mille (CPM): The standard advertising pricing model representing the cost advertisers pay per 1,000 advertisement impressions. Kontext’s reported $2.50 CPM compared to Facebook’s $7.35 CPM in comparative campaigns demonstrates competitive pricing advantages. Lower CPMs benefit advertisers by reducing acquisition costs while higher fill rates and better targeting can maintain or improve publisher revenue despite lower individual impression costs.
Click-through rate (CTR): The percentage of users who click on advertisements after viewing them, serving as a primary measure of advertising engagement and relevance. Kontext’s documented 1.58% CTR significantly exceeds industry averages for display advertising, typically ranging from 0.05% to 0.1%. Higher CTRs indicate better user engagement and typically correlate with improved campaign performance and advertiser satisfaction.
Advertising infrastructure: The technical systems, platforms, and networks that enable advertisement delivery, targeting, measurement, and optimization across digital channels. Kontext positions itself as next-generation infrastructure specifically designed for AI-powered applications, addressing gaps left by existing systems optimized for web and mobile platforms. This infrastructure includes real-time content analysis, dynamic creative generation, campaign management, and performance measurement capabilities.
Supply-side platform (SSP): Technology platforms that enable publishers to manage, sell, and optimize their available advertising inventory in automated auctions. Traditional SSPs work with pre-created advertising materials, while Kontext’s approach requires real-time creative generation capabilities. The company functions as both SSP and creative generation platform, representing a hybrid model adapted for AI application requirements.
Brand safety: Measures and controls ensuring advertisements appear alongside appropriate content that aligns with advertiser values and doesn’t damage brand reputation. AI-generated advertising content presents unique brand safety challenges since creative materials are produced dynamically rather than reviewed in advance. Kontext must implement sophisticated content analysis and filtering systems to ensure generated advertisements meet brand safety standards while maintaining contextual relevance and engagement effectiveness.
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Who: Kontext, a 13-person startup founded in 2023 by former entrepreneurs including Jan Matas (Deepnote co-founder) and Andrej Kiska (Credo Ventures co-founder), with over 400 AI research paper citations collectively.
What: $10 million seed funding round to expand AI-powered advertising platform that generates real-time, contextually relevant advertisements within AI chatbots and conversational interfaces, claiming 66% revenue increases for publisher partners.
When: April 1, 2025, with M13 leading the funding round and participation from Torch Capital, Credo Ventures, and Parable VC.
Where: The startup operates globally, serving publishers including DeepAI, Media Search, Pixel Chat, and Spicy Chat, with plans to expand across AI-powered consumer applications and platforms.
Why: Kontext addresses a missing advertising infrastructure layer for AI-powered applications, capitalizing on the economic reality that GenAI products require advertising-supported monetization to cover high inference costs while providing contextually relevant advertising experiences native to conversational interfaces.
