Every AI coding tool uses the same models. Our Context Engine is the difference.
Augment's Context Engine maintains a live understanding of your entire stack - across repos, services, and history. Agents that finish tasks, not just suggest lines.
1M+
Files indexed at once
Real-time
knowledge graph
Architectural
Awareness
trusted by teams shipping millions of lines of code
Why most agents fail on complex tasks
Most AI agents rely on grep to build context. They don't know what they don't know. They find files but miss architecture. Match strings but lose patterns.
Most AI agents rely on grep to build context. They don't know what they don't know. They find files but miss architecture. Match strings but lose patterns.
THE RESULT:
Agents that start strong but degrade quickly, requiring constant re-explanation and manual intervention.
GET LOST IN LIMITED CONTEXT:
Your architectural patterns
Dependencies across services
Edge cases buried in legacy code
Coding standards and conventions
Related files and configurations
The full picture of what you're building
GETS LOST IN LIMITED CONTEXT:
Your architectural patterns
Dependencies across services
Edge cases buried in legacy code
Coding standards and conventions
Related files and configurations
The full picture of what you're building
THE RESULT:
Agents that start strong but degrade quickly, requiring constant re-explanation and manual intervention.
Why context quality determines code quality
Augment generated pull requests that matched or exceeded human code quality, significantly outperforming competitors. The code worked on first try, required no follow- up, and followed existing patterns instead of creating new ones.
