Keenable's $26M Bet on Search Engines for AI
A new startup aims to reshape search engines to cater to AI, not humans.
Key points
- Keenable raised $26 million in seed funding in October 2023.
- It indexes over 100 billion web documents for AI use.
- Keenable partners with AI labs and inference providers.
- The startup aims to double its staff by the end of 2023.
Why is Keenable building a search engine for AI?
Keenable wants to make web searches better for AI tools, not just people. Traditional search engines like Google are built for humans who skim pages, but AI chatbots can read much more. Andrey Styskin and Matthias Petri, the brains behind Keenable, raised $26 million to change this, with funding led by Accel. They believe AI chatbots can work better if they have direct access to more web data.
How does Keenable's approach differ?
Keenable is creating a massive database of web documents, over 100 billion pieces, which AI developers can use. Their index helps AI programs find information quicker, making them more efficient. Styskin, who worked at Yandex and Amazon, says the goal is to cut the cost of these searches by using smarter indexing methods. This would make it easier for smaller companies to compete with giant search engines.
Who is using Keenable's technology?
Though Keenable hasn't named its clients, its tech is already in use. AI labs and companies use its search index in both development and real-time applications. Keenable recently teamed up with Gradium, a voice AI company, to enhance how AI retrieves information on the go.
What are the challenges ahead?
Building such a big search engine isn't cheap. Styskin admits it's costly, but he sees an opening for a smaller, innovative company to succeed where big names like Google might not focus. Keenable plans to double its team of 15 engineers by the end of the year. With giants like Google tweaking their search for AI, Keenable has competition, but it also shows there's room for new ideas.
Common questions
Why is AI search different from regular search?
AI search needs to handle more data and process it faster. Unlike people, AI can read and analyze vast amounts of information quickly, so they need search systems built for that purpose.
What does this mean for traditional search engines?
Traditional search engines may need to adapt. As AI use grows, engines that only serve human users could become less relevant, pushing giants like Google to innovate their offerings.
