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Atla

Atla

Automatically detect errors in your AI agents

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480 Upvotes

About

Atla is an AI agent improvement engine designed to help developers automatically detect, understand, and fix underlying issues in their AI agents quickly. It provides real-time visibility into agent interactions, identifies recurring failure patterns by clustering and ranking issues, and offers actionable suggestions for improvement. Users can test prompt, model, and architecture changes with confidence, comparing performance across versions. Atla integrates seamlessly with existing observability tools like Langfuse and LangSmith, and supports various AI frameworks and models, aiming to turn raw logs into actionable insights and measurable improvements for teams building and operating AI agents.


Color Palette

Dark Background

#121212

60%

Primary Text

#FFFFFF

30%

Accent Blue/Purple

#8A8AFF

5%

Accent Green

#4CAF50

2%

Typography

Sans-serif

Headings and Body

Aa

Design Review

The design of the Atla landing page is highly effective, leveraging a dark theme to create a modern, sophisticated, and tech-forward aesthetic. The contrast between the deep dark background and crisp white text ensures excellent readability. A vibrant blue/purple accent color is strategically used for calls to action, links, and key highlights, drawing the user's eye to important interactive elements without being overwhelming. The layout is clean and minimal, focusing on clear headings, concise descriptions, and relevant visual aids like screenshots and integration logos. The consistent use of a modern sans-serif font contributes to the overall professional and contemporary feel. The design successfully conveys the product's innovative nature and its focus on clarity and efficiency in debugging AI agents.

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