Tracellm is an observability platform for production AI applications. Monitor prompt execution, token consumption, latency, spans, errors, and model calls across your LLM workflows. Export traces using OpenTelemetry (OTLP) and quickly identify bottlenecks before they impact users
Hey Product Hunt! I'm Jyotishmoy, the maker of Tracellm.
Like many developers, I've been building AI applications using different LLMs and frameworks. One thing quickly became obvious: once an AI app reaches production, it's surprisingly difficult to understand what's actually happening.
Questions like:
Why did this request fail?
Which prompt caused the issue?
How many tokens did this interaction consume?
Where is the latency coming from?
Which model call is slowing everything down?
There are great observability tools for traditional applications, but I wanted something purpose-built for AI workloads.
That's why I built Tracellm.
Tracellm gives developers complete visibility into their AI applications by tracing prompts, spans, token usage, latency, model calls, and errors in one place. It also supports OpenTelemetry (OTLP), making it easy to integrate with your existing observability stack.
This is just the beginning. I have a lot more planned, including richer analytics, cost optimization insights, and support for more AI frameworks and providers.
I'd genuinely love your feedback:
What features would make this indispensable for your workflow?
Which AI framework or model provider should I support next?
What would you like to see improved?
Thanks so much for checking out Tracellm! I'm excited to answer your questions throughout the launch.
please give it a "⭐" in GitHub if you find this helpful.
About TraceLLM on Product Hunt
“OpenTelemetry for production AI applications”
TraceLLM launched on Product Hunt on July 31st, 2026 and earned 108 upvotes and 14 comments, placing #11 on the daily leaderboard. Tracellm is an observability platform for production AI applications. Monitor prompt execution, token consumption, latency, spans, errors, and model calls across your LLM workflows. Export traces using OpenTelemetry (OTLP) and quickly identify bottlenecks before they impact users
On the analytics side, TraceLLM competes within Open Source, Developer Tools, GitHub and Tech — topics that collectively have 1.3M followers on Product Hunt. The dashboard above tracks how TraceLLM performed against the three products that launched closest to it on the same day.
Who hunted TraceLLM?
TraceLLM was hunted by Jyotishmoy Deka. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of TraceLLM including community comment highlights and product details, visit the product overview.
Jyotishmoy Deka