Koah raises $5M seed funding to bring ads into AI-powered apps

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Koah raises $5M seed funding to bring ads into AI-powered apps
© Anastasia Usenko / Getty Images

Koah, a startup tackling the challenge of monetizing consumer AI apps, has raised $5M in seed funding led by Forerunner, with participation from South Park Commons and AppLovin co-founder Andrew Karam.

Founded by Nic Baird, Koah is building an advertising layer for AI chat applications — offering developers a way to cover inference costs and reach global audiences without relying solely on subscriptions.

Rethinking monetization in consumer AI

While early AI apps focused on premium subscriptions for prosumer users, Koah sees opportunity in emerging markets where users aren’t likely to pay $20/month but adoption is growing rapidly.

Koah’s ad platform is already integrated into apps such as Luzia (AI assistant), Heal (parenting app), Liner (student research tool), and DeepAI (creative platform). Advertisers include UpWork, General Medicine, and Skillshare, with ads designed to appear contextually within AI chats.

Baird says Koah’s ads deliver clickthrough rates of 7.5% — 4–5x higher than traditional mobile ad networks — with some early partners earning $10K in their first month.

“Once AI apps move beyond wealthy prosumer markets, ads are the only scalable way to make them profitable globally,” said Nic Baird, co-founder and CEO of Koah.

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Beyond banner ads

Rather than display-style advertising, the startup aims to match user intent with relevant offers inside conversations. For example, a startup founder asking an AI app about business strategy could see an UpWork ad for hiring freelancers.

Investor perspective

“Monetization is the elephant in the room for AI builders and investors,” said Nicole Johnson, Partner at Forerunner. “Subscriptions alone won’t sustain consumer AI, and ads will inevitably play a major role. Koah is building the essential monetization layer.”

With the new funding, the company plans to scale its ad network, grow its publisher base, and refine contextual targeting to make ads feel like part of the user experience.

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