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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
Exa Raises $250M Series C to Build the Search Engine for AIs
Exa Labs · 2026-06-26 · via Hacker News - Newest: "AI"

AI agents will search the web more than humans this year.

Exa just raised $250M at a $2.2B valuation led by a16z to power all agents with the highest quality web search.

Exa already powers search for Cursor, Cognition, HubSpot, OpenRouter, Monday.com and over 400,000 developers. These are the early days - in the next few years the number of searches from LLMs will be 1000x more than Google searches today. This is an opportunity to redesign how the world gets information.

We started Exa five years ago to build perfect search over all the world’s information, far beyond traditional search engines in quality and comprehensiveness.

In early 2023, we saw that AI products and AI agents would most benefit from a perfect search API, so Exa announced the first web search API for AI. Since then, the number of companies using Exa has grown to over 5,000.

Customers choose Exa because we’re the highest quality search API at every latency and price point.

Some examples:

  • GTM agents need extremely comprehensive search over people and companies, so we built comprehensive indexes over these verticals and can run for minutes to gather all the data agents need.
  • Coding agents need complex searches over public code / technical documentation, so we finetuned special embedding models for code search.
  • Everyone wants their chat agents to be faster and cheaper, so we built the fastest search API in the world (sub200ms) and fast text extraction models which reduce LLM token counts by over 20x.

Exa quality benchmarkExa quality vs latency

This is only possible because we spent years building a web-scale search engine from scratch. Our crawlers track over 500 billion urls, our research teams train special embedding models on a GPU cluster we assembled, and we’ve built new vector databases for the extremely high QPS that agents need. There’s a reason there are more space programs than independent search engines.

Most other search providers actually wrap other search engines and therefore cannot compete on quality/latency/cost. As we scale up infra and model training in the coming months, the gap between Exa and wrappers will become clearer. For example, six months ago we were worse than Google at code search, and now we’re used by nearly every coding agent.

With this funding, we’re going to train our next-gen class of models and scale our infrastructure to handle 100s of thousands of searches per second. We’re assembling the best people around the world to do this. Recent hires include the head of retrieval infra from Meta, head of search backend at Yandex, and a research team out of Google.

We're also scaling our go-to-market org. Marcus Holm, President of LaunchDarkly, is joining as Exa’s CRO to lead our global GTM organization. We're hiring across sales, solutions, and marketing worldwide.

As trillions of agents come online over the coming years, search needs will grow thousands of times beyond the total search volume of Google. And as agents make increasingly important business decisions, their requirements for comprehensiveness, freshness, and precision will far exceed what humans require. In short, agents will need perfect search over all the world’s information at an unprecedented scale.

Building a perfect search engine will be extremely hard. It's also necessary. Information is critical civilizational infrastructure for our new AI reality. Politics is fragmenting, wars are raging, and AI is accelerating -- we need tools we can trust that deeply inform us what's going on. If we can build perfect search so that every AI has the highest quality information, then every human will too.