Gravity has raised a US$30.5 million Series A to expand an advertising platform built for AI chatbots, assistants, agents, and search experiences. The round was co-led by Lightspeed Venture Partners and Committed Capital, bringing the company’s reported total funding to US$38.5 million.
The funding puts more capital behind a question that AI product developers are increasingly facing: how do conversational products make money without simply copying the display-ad model of the open web? Gravity’s answer is a full-stack marketplace that connects brands seeking AI-native inventory with developers looking to monetize AI interactions.
Key Takeaways
- Gravity raised US$30.5 million in Series A funding and has reported US$38.5 million in total funding.
- The company operates advertiser buying tools, publisher monetization infrastructure, an exchange, measurement, and creative support for AI advertising.
- For marketers, the more important test is whether conversational context can become a scalable ad signal without damaging the usefulness of AI products.
Table of contents
Jump to each section:
- What Gravity is building
- Why the full-stack model matters
- Where AI advertising is headed
- What marketers should watch
What Gravity is building
Gravity positions itself as advertising infrastructure for AI products rather than a conventional display network. Its documentation describes a system where an AI application sends recent conversation context to Gravity, the platform matches eligible ads, runs an auction, returns a relevant placement, and pays the publisher for the impression.
On the advertiser side, Gravity offers demand-side buying tools alongside campaign measurement and ad-creation capabilities. On the publisher side, developers can use the platform to monetize AI apps. The exchange connects the two sides, giving Gravity control over more of the transaction than a standalone ad-buying or publisher tool would have.
Reported advertiser clients include Best Buy, Target, Vercel, and MongoDB. Gravity also lists support for AI chat, coding assistants, consumer applications, and AI search use cases in its product documentation.
The company says relevance is based on conversational context rather than keyword matching. That distinction matters because an AI conversation can reveal a user’s problem, constraints, and stage of consideration more clearly than a single search query, although turning that signal into consistent ad performance still has to be proven at scale.
Why the full-stack model matters
Gravity’s pitch is partly about network economics. By operating infrastructure for advertisers and AI publishers at the same time, the company can potentially learn from both demand and supply as its marketplace grows.
Co-founder Zach Oldham told Business Insider, “Because we’re owning the full stack, we benefit from true network effects as we scale.”
That model could be useful for smaller AI products that want monetization without building their own ad systems or direct sales teams. It also gives advertisers a single route into multiple AI surfaces rather than requiring separate integrations with every chatbot, assistant, or agent.
The risk is that owning more of the stack does not automatically create enough high-quality inventory or advertiser demand. Gravity is still an early-stage company, and the emerging AI advertising market includes larger adtech platforms and major technology companies experimenting with their own approaches.
Where AI advertising is headed
One sign that conversational advertising is moving beyond theory is that major brands are already testing placements inside AI products. In February 2026, Target said it was among the first companies working with OpenAI on contextual ads in ChatGPT, with testing beginning that month.
That experiment is separate from Gravity, but it illustrates the broader shift the startup is betting on. AI interfaces increasingly sit between a user’s question and a purchase decision, creating a new point where brands may want visibility.
Gravity is also testing what it describes as agent-to-agent advertising. In that model, an advertiser can provide structured product information, features, and promotions that another AI agent can use when helping a person make a decision. The company is exploring purchase flows as well, with user approval required before a transaction is completed.
For marketers, this moves the discussion beyond inserting sponsored text into a chatbot. The longer-term opportunity is to make product information usable by AI systems at the moment they are comparing options, recommending products, or helping complete a task.
What marketers should watch
The immediate appeal of AI-native advertising is context. A conversational interface may offer richer signals than a page view or keyword because it captures what the user is trying to accomplish and what has already been discussed.
But the same context creates a higher bar for relevance. An ad that interrupts a useful AI interaction can feel more intrusive than a conventional sponsored result. Platforms will need clear controls over placement quality, brand safety, privacy, and measurement if marketers are going to move meaningful budgets into the channel.
Gravity’s documentation says publishers can set relevance thresholds and exclusions, while its measurement stack supports pixel and server-side conversion tracking. Those are familiar adtech mechanics applied to a less familiar interface.
The US$30.5 million round gives Gravity more resources to build out that infrastructure, but funding alone does not establish a durable new channel. The marketer test is simpler: whether AI placements can produce measurable outcomes while preserving the experience that made users choose conversational products in the first place.
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