Multi-agent review catching bugs early in AI-generated code
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale.
Claude Code analyzes uploaded code files and provides detailed feedback on authentication errors, token handling, request interceptors, and optimization opportunities. Users can ask Claude to examine specific files, identify root causes, and suggest fixes—enabling faster debugging than manual review.
Claude Code can reference large amounts of code context (equivalent to 100K lines) through projects, enabling it to understand architectural patterns and enforce consistency. Teams can use Claude Code to review changes against organizational standards and suggest refactoring.
Claude Code explains programming concepts, walks through code logic, and provides best-practice recommendations. Users can paste code snippets or upload files to receive conversational guidance on implementation patterns and architectural decisions.
Claude Code automates routine code review feedback, generates documentation, and handles Git workflows through natural language commands. This frees developers to focus on complex logic and architectural decisions rather than repetitive review cycles.
Claude Code integrates into the terminal and development workflow, allowing developers to describe features in natural language and receive code suggestions, Git workflow automation, and task execution. This reduces time spent on routine coding tasks and boosts productivity.