traceAI

What is traceAI?

traceAI is an open-source observability framework for AI applications built on OpenTelemetry. It records each LLM call, prompt, token count, retrieval step, tool call and agent decision as structured traces, so when an answer goes wrong you can see which retrieval missed or which tool returned stale data. The traces can be sent to any OpenTelemetry-compatible backend such as Datadog, Grafana, Jaeger or Future AGI, so you do not need to adopt a new vendor or dashboard. The project provides drop-in instrumentation for more than 50 AI frameworks across Python, TypeScript, Java and C#, with consistent semantic conventions for LLM calls, agents, tools, retrieval and vector databases. The README says setup takes about three lines of code. It is Apache-2.0 licensed and made by Future AGI.

Use cases

• Trace LLM calls in production
• Debug a wrong agent answer
• Monitor token use and prompts
• Send AI traces to Datadog or Grafana
• Instrument RAG pipelines

Who it's for

• AI engineers
• Backend developers
• Platform and SRE teams
• LLM app builders

Why use traceAI

• Pinpoints failures in agent runs because every step is captured as a span.
• Avoids vendor lock-in as traces go to any OpenTelemetry backend.
• Quick to adopt, needing roughly three lines added to existing code.
• Fits mixed stacks with consistent APIs across four languages.

traceAI features

• OpenTelemetry-native traces
• 50+ framework integrations
• Support for Python, TypeScript, Java and C#
• Semantic conventions for LLMs, agents, tools and retrieval
• Works with any OTel-compatible backend
• Drop-in setup with a few lines of code
• Captures prompts, completions and token counts

How to get started with traceAI

1. Install the traceAI package for your language, such as the Python or TypeScript library.
2. Add the few lines of setup code that register the instrumentation for your AI framework.
3. Point the exporter at your OpenTelemetry backend, such as Grafana or Datadog.
4. Run your app and open the traces to inspect prompts, tool calls and retrieval steps.

traceAI limitations

• You still need a backend to store and view traces
• Prompts and completions in traces may contain sensitive data you need to manage

traceAI pricing

traceAI is open source, so you can use and self-host it for free.

Prices can change and may vary by country or exclude tax. Check the official pricing page.

traceAI alternatives

The main traceAI alternatives listed on Debuly are Langfuse, Arize Phoenix, Helicone, Opik, Braintrust and OpenLIT. The table compares pricing and platforms; order is A–Z.

1. 

   Arize Phoenix

   Open-source tool for tracing, evaluating and experimenting on LLM apps and agents, free to self-host or run locally.

   Developer platformsAutomation and agents
   Open sourceVisit Arize Phoenix (official site)
2. 

   Braintrust

   AI observability and evaluation platform for tracing LLM apps and agents, scoring outputs and catching regressions before release.

   Developer platformsCoding
   FreemiumVisit Braintrust (official site)
3. 

   Helicone

   Open-source LLM observability and AI gateway that logs requests, tracks cost and latency, and routes to 100+ models through one API.

   Developer platformsCoding
   FreemiumVisit Helicone (official site)
4. 

   Langfuse

   Open-source LLM observability and evaluation platform for tracing agents, managing prompts and scoring outputs.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Langfuse (official site)
5. 

   OpenLIT

   Open-source, OpenTelemetry-native platform for tracing, evaluating and guarding AI agents, with cost and GPU monitoring

   Developer platformsCodingAutomation and agents
   Open sourceVisit OpenLIT (official site)
6. 

   Opik

   Comet's open-source platform for tracing, evaluating and monitoring LLM applications and agents, self-hosted or in the cloud.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Opik (official site)

traceAI FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from app.futureagi.com · fetched 24 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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