We're an AI research lab building a search engine for the future
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Introducing Exa 3.0: our largest ever improvement to search quality.
Exa is now #1 on every benchmark we tested, from public evals to verticals like coding and GTM intelligence.
It's the result of multiple research breakthroughs 🧵
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Exa retweeted
Introducing Exa 3.0: our largest ever improvement to search quality.
Exa is now #1 on every benchmark we tested, from public evals to verticals like coding and GTM intelligence.
It's the result of multiple research breakthroughs 🧵
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156
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192,039
Introducing Exa 3.0: our largest ever improvement to search quality.
Exa is now #1 on every benchmark we tested, from public evals to verticals like coding and GTM intelligence.
It's the result of multiple research breakthroughs 🧵
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Exa 3.0 highlights make agents more accurate on search tasks, using 95% fewer tokens than full text.
Instead of extracting highlights from each page individually, our new model selects tokens across all results, giving more to the best pages and cutting repeated information.
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Exa 3.0, Exa Lite, upgraded highlights, and our expanded index are available today through the API.
Read more: exa.ai/blog/exa-3
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💪
Exa just passed $100m in annualized revenue.
We've grown almost exactly 10x per year for 3 years. We now handle 2 billion requests a month from 200k+ teams. And it’s still so early:
We predict agents will search 1000x more than humans by 2030.
Agents don't search like humans. They write long, complex queries and want all the world's data, not just the web. We've spent 5 years building a search engine designed for them.
We now serve personal agents, AI labs, coding agents, GTM agents, really any agent. Exa gives these agents access to 100s of billions of web documents and tons of proprietary data.
Our customers are increasingly noticing that information is the bottleneck to agent performance. While the world seems close to perfect intelligence with models like Fable and Astra, we are very far from perfect information.
To our small but legendary team, thank you for getting us here, from engineering to research to GTM to ops.
To our customers, it is an honor to serve you. We have some exciting releases coming soon and can't wait to share them 🫡
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Exa retweeted
Exa just passed $100m in annualized revenue.
We've grown almost exactly 10x per year for 3 years. We now handle 2 billion requests a month from 200k+ teams. And it’s still so early:
We predict agents will search 1000x more than humans by 2030.
Agents don't search like humans. They write long, complex queries and want all the world's data, not just the web. We've spent 5 years building a search engine designed for them.
We now serve personal agents, AI labs, coding agents, GTM agents, really any agent. Exa gives these agents access to 100s of billions of web documents and tons of proprietary data.
Our customers are increasingly noticing that information is the bottleneck to agent performance. While the world seems close to perfect intelligence with models like Fable and Astra, we are very far from perfect information.
To our small but legendary team, thank you for getting us here, from engineering to research to GTM to ops.
To our customers, it is an honor to serve you. We have some exciting releases coming soon and can't wait to share them 🫡
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We sat down with @3blue1brown to discuss our research vision of "Attention over all the world's information."
Plus why knowledge should not live in model weights, the compression trick behind cheaper retrieval, and why we hire through work trials.
1:20 – What is “attention over everything”?
4:46 – A knowledge graph of the whole web
11:32 – How do you evaluate search for AI agents?
15:13 – Why not put everything in the weights?
22:55 – Why Exa hires through work trials
25:15 – The compression trick behind cheaper retrieval
27:40 – Dealing with misinformation
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We built ATLAS, a web search benchmark for how agents actually search today.
Existing agentic search benchmarks are often outdated, contaminated, or saturated. ATLAS is designed to separate strong search from weak search.
Learn more: exa.ai/blog/atlas-benchmark
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ATLAS tasks require many sources to retrieve fresh or niche information.
Questions are synthetically generated through an automated pipeline based on real-world search trends, covering 20+ topic categories.
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Even the top search agents set to the highest effort modes cannot find 1/3 of the verified information.
Read the full research: exa.ai/blog/atlas-benchmark
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We just added 211 million restaurants, museums, and parks to Exa's index.
Give your AI agents access to search over all the places in the world with structured data including opening hours, reviews, and phone numbers.
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Exa Places significantly improves the accuracy of personal agents that are performing tasks with local intent.
It has the highest accuracy across search providers we evaluated.
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Exa Places is live across all our endpoints at no additional cost!
Learn more
exa.ai/blog/places-search
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Introducing Agent Ultra - a step change in deep research
Agent Ultra orchestrates swarms of agents to perform exhaustive research, build comprehensive lists, and answer questions requiring thousands of sources.
In both evals and vibes, it's state of the art
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You can use Agent Ultra in the Exa API today!
Learn more - exa.ai/blog/exa-agent-ultra
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