获 Accel 支持的 Keenable 正为 AI Agent 构建全网索引

搜索引擎是为人类构建和优化的，因为人们无法投入足够的时间或注意力来浏览完整网页。但随着人们越来越多地使用 AI 聊天机器人搜索网络和完成任务，有一种观点认为，互联网现有基础设施需要更新，以便优先服务 AI——因为这些机器人能够阅读和处理范围大得多的信息。

曾领导俄罗斯搜索巨头 Yandex 搜索、AI 与云业务部门的 Andrey Styskin，以及德国 AI 科学家 Matthias Petri，正通过他们的新创业公司 Keenable 解决这一问题。该公司近日结束隐身运营，并完成 2600 万美元种子轮融资。本轮融资由 Accel 领投，Conviction Partners 和多位天使投资人参投。

在 Styskin 看来，AI 聊天机器人如果能够利用源文档来锚定其回答，通常会有更好的表现。他告诉 TechCrunch：“这实际上形成了一个不同于 Google 从人类行为中学到的新飞轮。”

Keenable 表示，其已构建一个包含超过 1000 亿份文档的网页搜索索引；其 API 已被多家 AI 实验室和推理服务商用于生产环境中的训练和运行时阶段。这家创业公司不愿透露客户身份，但近期已与语音 AI 公司 Gradium 达成合作伙伴关系，以支持实时信息检索。

凭借在 Yandex 和 Amazon 从事搜索业务长达 20 年的经验，Styskin 解释了 Keenable 的产品为何不同于企业搜索解决方案：后者在扩展至网页规模时可能失效，并且成本极高。“如果你不针对特定任务微调索引结构，那么由于数据规模过于庞大，服务和扫描整个互联网的成本会非常高。因此，你需要在如何基于查询极快地缩小搜索空间方面进行创新。这正是我们带来的能力。”他说。

领投本轮融资的 Accel 合伙人 Zhenya Loginov 表示，在网页规模搜索基础设施方面，AI 公司可选方案极少，尤其是在 Google 和 Microsoft 为避免自身业务被蚕食，正着手关闭其现有搜索 API的情况下。相反，这些科技巨头正采取更为捆绑的策略，并谨慎选择合作伙伴。

对 Styskin 而言，这些决定印证了他在 Amazon 时看到的机会。当时，他与 Petri 共同为 Alexa 等 AI 应用构建网页搜索基础设施。他注意到，Cloudflare 的数据显示，AI 爬虫在搜索流量中所占比例正不断增长；他开始意识到，可以开发一套从设计之初就面向 AI 的网页搜索基础设施。

凭借这些经验，Styskin 利用自己的人脉网络，为这家新创业公司招募了几名前同事。公司也在构建专有检索能力，其中包括即将推出的产品 Web Query Language。该产品将帮助 AI 系统综合来自多个网页来源的信息来回答问题，即使这些来源中没有任何一个包含完整答案。

成本将是这场竞争的重要变量。Styskin 表示，虽然要说服人们放弃 Google 进行搜索“极其困难”，但创新者的窘境意味着，这家美国巨头在 Agent 查询领域或许“可以被击败”；Keenable 这样规模较小的公司可以进行创新，并向 AI 公司提供成本效率更高的解决方案。

不过，构建庞大搜索索引的成本确实高昂。“别问——贵得令人痛苦。”他说。但他表示，这家创业公司正尽力控制成本，并循序渐进地推进。目前公司在美国和欧洲拥有 15 名工程员工，计划利用这笔新资金在今年年底前将员工人数翻倍，以建立其市场进入能力。

在实现成为“AI Agent 的下一代 Google”这一梦想之前，这家创业公司还有很多步骤要走。其他玩家也已进入这一领域，例如 Brave 和 Exa；而 Google 自身也正在为 AI 时代重塑搜索体验。但这一更广泛的趋势表明，Keenable 的判断也得到了 Googleplex 的认同：无论搜索服务的是人类还是 Agent，“十个蓝色链接”的时代可能正走向终结。

Search engines were built and optimized for people, who can’t spare the time or attention required to scan entire web pages. But as people increasingly use AI chatbots to search the web and do tasks, there’s a line of thinking that the internet’s current infrastructure needs to be updated to cater to AI instead, as these bots can read and process much larger portions of information.

Andrey Styskin, who previously led Russian search giant Yandex’s search, AI, and cloud division, and German AI scientist Matthias Petri are working to solve that problem with their new startup, Keenable. The company recently came out of stealth with $26 million in seed funding. Accel led the funding round, which also saw participation from Conviction Partners and some business angels.

From Styskin’s perspective, AI chatbots tend to do much better if they can ground their responses with source documents. “This actually creates a new flywheel that is different from what Google learned from human behavior,” he told TechCrunch.

Keenable says it has been building a web search index of more than 100 billion documents, and its API is already used in production at several AI labs and inference providers during both training and runtime. The startup wouldn’t disclose who its customers are, but it recently struck a partnership with voice AI company Gradium to support live information retrieval.

Drawing from his experience of 20 years building search at Yandex and Amazon, Styskin explained how Keenable’s product is different from enterprise search solutions that can break down and prove very costly at web scale. “If you do not fine-tune your index structures for a specific task, the cost of serving and scanning the whole internet is enormous because of the volume. That’s why you need to innovate on how you can narrow the search space based on your query very fast. This is what we are bringing to the table,” he said.

According to Accel partner Zhenya Loginov, who led the investment, AI players have very few options when it comes to web-scale search infrastructure, especially with Google and Microsoft taking steps to shut down their existing search APIs to avoid cannibalization. Instead, the tech giants are opting for a more bundled approach, and being selective about their partners.

To Styskin, these decisions confirmed the opportunity he saw when he was at Amazon, working with Petri on web search infrastructure for AI applications such as Alexa. He’d seen Cloudflare data that AI crawlers were responsible for a growing share of search volume, and started realizing that there was an opportunity to develop web search infrastructure that is built with AI in mind.

Armed with that experience, Styskin tapped into his network to hire a handful of former colleagues for his new startup, which is also building proprietary retrieval capabilities. This includes an upcoming product, Web Query Language, which would help AI systems answer questions by combining information from various web sources, even when none contain the full answer.

Costs will be an important part of the equation. Styskin says while it is “extremely hard” to convince people to move away from Google for search, the innovators’ dilemma means that the U.S. giant is potentially “beatable” on agentic queries, and a smaller company like Keenable can innovate and offer a more cost-efficient solution to AI companies.

Still, the costs of building a giant search index are real. “Don’t ask — it is painfully expensive,” he said. But, he says the startup is doing its best to keep costs in check and pace itself. With a team of 15 engineering staff across the U.S. and Europe, the company plans to use the fresh cash to double its headcount by the end of the year to build its go-to-market motion.

There are many more steps before the startup can achieve its dream of becoming “the next Google for AI agents.” Other players have entered the space, such as Brave and Exa; and Google itself is overhauling its search experience for the AI era. But this broader motion indicates that Keenable’s conviction is also shared at the Googleplex: Whether it’s for humans or for agents, the era of the “ten blue links” may be coming to a close.