Coolhand Labs provides continuous monitoring and automated remediation for production LLM agents, detecting silent failures, cost spikes, and quality regressions in real time. The platform instruments your codebase, surfaces feedback, and generates pull‑request fixes that reduce token spend by 50–70% while maintaining HIPAA compliance. Teams can review the suggested changes, keep their agents performant, and avoid manual debugging of costly AI workloads.
Funding
Funding not disclosed
Founders
Product
Problem
Production AI agents often consume large numbers of tokens without delivering value, and silent failures can go unnoticed until they impact user experience or inflate costs. Detecting these inefficiencies and failures typically requires manual log analysis and ad‑hoc debugging, which diverts engineering resources and delays remediation.
Solution
Coolhand Labs continuously monitors LLM agents in production to identify token‑draining inefficiencies and silent failures as they occur. When an issue is detected, the platform automatically creates a pull request containing a suggested code fix, allowing developers to review and merge the change with minimal effort. Integration is achieved through an open‑source skill that instruments the codebase, adds request tracing, and captures passive human feedback without adding heavyweight dependencies. The service also provides cost‑per‑unit work metrics and quality trend analysis based on custom value assumptions, enabling teams to quantify and improve agent performance. A generous free tier is available, and the platform is designed to meet HIPAA compliance requirements for handling sensitive data.
Target Audience
Primary customers are engineering teams and product groups that deploy LLM‑powered applications and need automated cost control and quality monitoring for their AI agents.
Features
- Real‑time monitoring of token usage and detection of silent agent failures in production environments
- Automatic generation of fix pull requests that developers can review and merge directly in their repositories
- Open‑source skill for low‑dependency integration that instruments code, adds LLM request tracing, and captures passive human feedback
- Cost‑per‑unit of work analytics with customizable value assumptions and quality trend visualizations
- HIPAA‑compliant data handling to protect protected health information
- Free tier with no credit‑card requirement, enabling immediate adoption and evaluation