TraceLLM
To provide a purpose-built observability layer for AI applications, enabling developers to trace and understand AI workflows in production.
At a Glance
- AI Engineers
- Full-stack Developers
- DevOps teams
- AI Startups
AI Tools by TraceLLM
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TraceLLM
Open Source AI Observability Platform
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Products & Services
An observability platform for monitoring AI application performance, tracing prompts, spans, token consumption, and errors.
SDK for integrating AI application tracing with the TraceLLM platform, available via npm as @use-tracellm/sdk-node.
A UI for inspecting and investigating AI application traces and session data.
Market Position
A developer-centric, OTLP-native observability solution specifically designed for the unique tracing requirements of LLM-based applications.
Leadership
Founders
Jyotishmoy Deka
Full Stack Engineer at Cogneo Technologies and creator of TraceLLM. Experienced in building scalable systems with React, Go, and Node.js. Previously at Tax Hummer.
Executive Team
Jyotishmoy Deka
Founder
Full Stack Engineer with a focus on AI observability and developer tools.
Founding Story
Built by Jyotishmoy Deka to solve the visibility gap in production AI applications, where understanding failure modes and performance bottlenecks is often difficult.
Business Model
Revenue Model
Currently offered as a free and open-source tool, focusing on community adoption.
Pricing Tiers
Access to tracing, spans, token monitoring, and OTLP exports.
Target Markets
- AI Engineers
- Full-stack Developers
- DevOps teams
- AI Startups
- Debugging failing LLM requests
- Monitoring token costs and consumption
- Analyzing latency in complex AI agent workflows
- Identifying 'confidently wrong' AI answers through trace analysis