CodeKarma is a production intelligence platform that maps real-time runtime behavior directly to source code, giving engineering teams and AI agents a precise understanding of how systems actually operate in production. The platform monitors 100% of requests with zero performance overhead, correlating errors to specific deployments and identifying dead code paths that traditional observability tools miss.
- Artificial Intelligence
- Data & Analytics
- Developer Tools
- Software Only
Funding
Funding not disclosed
Founders
Product
Problem
Modern software engineering teams struggle to understand how their systems actually behave in production. While code is written and deployed at increasing speed, the gap between what developers think their code does and what it actually does in runtime environments creates blind spots, especially as AI agents begin writing and evolving codebases. Traditional observability tools provide logs, traces, and metrics, but fail to connect runtime behavior back to the specific code that produced it, leaving teams unable to confidently identify dead code, diagnose errors, or understand which tests matter.
Solution
CodeKarma delivers production intelligence by mapping runtime behavior directly to the code that generates it, creating a single source of truth for engineering teams. The platform monitors 100% of requests with zero performance overhead and no blind spots, capturing golden signals, distributions, and execution paths without sampling. CodeKarma's deterministic root cause analysis uses 100% production data rather than hallucinations, correlating errors to specific deployments and identifying which tests exercise production-relevant paths. The platform is AI-native from day one, providing an MCP server that gives AI coding agents production context so they can evolve code safely and accurately.
Target Audience
Primary customers are software engineering teams, engineering managers, and VPs at companies with complex production systems, as well as AI agent developers and platform teams who need production intelligence to safely evolve codebases.
Features
- Execution path tracking that shows how code actually runs in production, including retired features, untaken paths, and dead classes never invoked
- Golden signals and distributions with full-fidelity monitoring of 100% of requests at zero performance cost
- Deployment error analysis that correlates errors to specific deploys for deterministic root cause identification
- Real test coverage metrics showing which tests exercise production-relevant paths versus those that don't
- KarmaPulse surface that surfaces the most important issues with specific recommended actions for remediation
- MCP server integration providing production context directly to AI coding agents, ensuring 100% data-driven responses with no hallucinations
- JetBrains (IntelliJ) and VS Code extensions for seamless developer workflow integration