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Why Deep Research Agents Fail: Lessons from GAIA

Find and fix AI agent failures

The agent observability and evals platform that dives deeper. Automatically detect errors and get insights to continually improve agent performance.
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Example screenshot of the atla platform
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Microsoft, Y Combinator, CreandumCohere, Meta, Deepmind
1
Find error patterns across your agent traces to understand why your agent fails.
A screenshot of Atla monitoring the errors in your agent
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2
Zoom into your traces to see the specific steps your agent took summarized, as well as to locate the specific error.
Screenshot of a trace view showing a tool error in an LLM agent
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3
Receive suggested fixes based on error patterns.
A screenshot of a pattern detected in an LLM agent with a suggested fix
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4
Run experiments and compare performance to confidently improve your agents.
A screenshot of comparing two different LLM model performances in the Atla tool
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A screenshot of comparing two different LLM model performances in the Atla toolA screenshot of a pattern detected in an LLM agent with a suggested fixScreenshot of a trace view showing a tool error in an LLM agentA screenshot of Atla monitoring the errors in your agent

See why your agents fail.

Install the Atla package
Track your agents
Understand errors instantly
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