Neatlogs is an AI observability platform that helps teams monitor, debug, and improve AI agent runs by importing traces from existing tools and enriching them with business context. It automatically detects failures across every run and groups related cases into single incidents, enabling faster root-cause analysis. The platform is trusted by teams at VWO, AB Tasty, Runway, and CFO.ai.
Funding
Funding not disclosed
Founders
Product
Problem
AI agent runs are complex, multi-step processes that often fail in ways traditional monitoring tools miss. Teams lack visibility into the full context of agent behavior, including customer feedback and business logic, making it difficult to identify root causes and resolve incidents quickly.
Solution
Neatlogs provides an AI observability platform that imports traces from existing tools or allows direct instrumentation, then enriches those traces with customer feedback and business context. The platform monitors every agent run, automatically surfaces failures, and groups related cases into a single incident for streamlined troubleshooting. By connecting technical trace data with business context, Neatlogs gives teams a complete picture of what happened and why, reducing time-to-resolution and improving agent reliability.
Target Audience
Primary customers are engineering and product teams building and operating AI agents, including those at companies like VWO, AB Tasty, Runway, and CFO.ai, who need observability into complex agent workflows.
Features
- Trace import from existing platforms or direct instrumentation for flexible integration
- Context enrichment by connecting customer feedback and business logic to agent runs
- Automatic failure detection across every run with incident grouping for related cases
- Detailed run visualization showing step counts, durations, and detection alerts
- Live trace monitoring with production-level visibility into agent behavior