traceAI

Name: traceAI
Brand: traceAI
Price: 4 USD

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Open-source observability for AI applications, tracing every LLM call, prompt, and agent decision.

From $4/mo (free plan available)

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Tracked since 2026

The Bottom Line

Updated May 26, 2026

Price: From $4/mo (free plan available). Compare plans

Key facts

Open-source AI tracing built on OpenTelemetry.
Captures LLM calls, prompts, tokens, and agent decisions.
Integrates with existing OTel-compatible observability backends.

Pros

Leverages existing observability infrastructure (OpenTelemetry-native)
Supports multiple programming languages and AI frameworks
Provides deep, granular insights into AI application behavior
Easy to integrate with minimal code changes
Open-source and community-driven

Cons

Requires familiarity with OpenTelemetry concepts for advanced usage
Initial setup might involve configuring environment variables and API keys
Relies on external observability platforms for data visualization and analysis

What is traceAI?

traceAI is an open-source AI tracing framework built on OpenTelemetry, designed to provide full visibility into AI applications. It captures detailed information about every LLM call, prompt, token count, retrieval step, and agent decision, transforming this data into structured traces. These traces are then sent to any OpenTelemetry-compatible backend, such as Datadog, Grafana, Jaeger, or Future AGI, allowing users to leverage their existing observability tools without needing new vendors or dashboards. The tool is ideal for developers and teams building AI applications who need deep insights into the performance and behavior of their LLMs, agents, and other AI components. It supports over 50 AI frameworks across Python, TypeScript, Java, and C#, offering zero-config tracing and consistent APIs. By providing rich context including prompts, completions, tokens, model parameters, and tool calls, traceAI helps in debugging, optimizing, and understanding complex AI workflows in production environments.

Available on: Web

Louis Corneloup Updated May 26, 2026 · how we evaluate Source github.com ↗

Key Features

Standardized tracing for AI workflows using OpenTelemetry spans and attributes
Zero-config setup with drop-in instrumentation for minimal code changes
Multi-framework support with 50+ integrations across Python, TypeScript, Java, and C#
Vendor-agnostic, compatible with any OpenTelemetry backend (e.g., Datadog, Grafana, Jaeger)
Rich context capture including prompts, completions, tokens, and model parameters
Production-ready with async support, streaming, error handling, and performance optimization

Pricing Plans

Free Trial

Pricing checked Oct 9, 2026

traceAI plans and prices, checked October 2026
Plan	Price	Details
Free	$0 USD per month	Unlimited public/private repositories Dependabot security and version updates 2,000 CI/CD minutes/month (Free for public repositories) +5 more Show less 500MB of Packages storage (Free for public repositories) Issues & Projects Community support GitHub Copilot Access GitHub Codespaces Access
Team	$4 USD per user/month	Everything included in Free Access to GitHub Codespaces Repository rules +11 more Show less Multiple reviewers in pull requests Draft pull requests Code owners Required reviewers Pages and Wikis Environment deployment branches and secrets 3,000 CI/CD minutes/month (Free for public repositories) 2GB of Packages storage (Free for public repositories) Web-based support GitHub Secret Protection GitHub Code Security
Enterprise	$21 USD per user/month	Everything included in Team Data residency Enterprise Managed Users +7 more Show less User provisioning through SCIM Enterprise Account to centrally manage multiple organizations Environment protection rules Repository rules Audit Log API SOC1, SOC2, type 2 reports annually FedRAMP Tailored Authority to Operate

Calculate your cost View full pricing

Is traceAI worth the price?

Good value

This pricing structure is generous, especially with its robust Free tier offering unlimited repositories and significant CI/CD minutes.

The Team tier at $4 per user/month provides excellent value for growing teams needing more advanced collaboration and security features. It's best for individual developers and small to medium-sized teams looking for a cost-effective, feature-rich observability solution.

Hidden Costs & Gotchas

CI/CD minutes overages

Packages storage overages

Full traceAI pricing: every plan, hidden costs and alternatives

How traceAI's pricing compares

At $4/user/mo, traceAI is the most affordable of its 4 comparable direct competitors.

traceAI

$19

$50

$60

$100

Entry paid plan, monthly, per user. Pricing checked Oct 9, 2026.

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traceAI FAQ

How does traceAI ensure compatibility with various AI frameworks and programming languages?

traceAI achieves broad compatibility by offering specific instrumentors for over 50 AI frameworks across Python, TypeScript, Java, and C#. These instrumentors provide consistent APIs and are designed for zero-config setup, allowing developers to easily integrate tracing into their existing AI applications regardless of the underlying framework or language.

What kind of data does traceAI capture from an AI application, beyond basic LLM calls?

Beyond basic LLM calls, traceAI captures rich contextual data including the full prompt, completion details, token counts, model parameters, tool calls made by agents, and decisions made during agent execution. It also traces retrieval steps in RAG (Retrieval Augmented Generation) systems, providing a comprehensive view of the AI workflow.

Can traceAI be used with a custom OpenTelemetry collector or a self-hosted OpenTelemetry backend?

Yes, traceAI is built on OpenTelemetry and is designed to be vendor-agnostic. This means it can send structured traces to any OpenTelemetry-compatible backend, including custom OpenTelemetry collectors or self-hosted solutions, in addition to popular commercial offerings like Datadog, Grafana, and Jaeger.

What are the specific environment variables or configuration steps required to get traceAI working with an OpenAI application?

For an OpenAI application, you typically need to set FI_API_KEY, FI_SECRET_KEY (for traceAI's own backend if used, or for project registration), and OPENAI_API_KEY. After installing the relevant traceai-openai package, you register a tracer provider and then instrument the OpenAI client, which automatically captures tracing data.

Source: github.com

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