Tracium provides an observability layer for AI systems, designed to give developers real-time visibility into the behavior, performance, and costs of AI agents. It addresses the need for clear monitoring and evaluation of AI operations, allowing for immediate insight with minimal setup. Integration is streamlined, requiring only a single line of code and installation of the Tracium SDK, making it accessible for rapid deployment without complex infrastructure changes.
The platform offers a range of features focused on tracking and optimizing AI workflows. Users can monitor token spend, infrastructure costs, and latency metrics across models, agents, and workflows in real time. Tracium enables tracing of every request end-to-end, capturing tool hops, agent steps, and model invocations. It also provides tools to capture, classify, and replay errors, detect drift in inputs and outputs, and compare prompts, models, and routing strategies using live traffic and outcome metrics. Per-tenant analytics allow for detailed slicing of usage, cost, latency, and outcomes by customer, workspace, or environment, supporting multi-tenant SaaS applications and accurate billing. Team collaboration features, access controls, and security measures such as data encryption in transit and at rest are included.
Tracium is delivered as an SDK that integrates with the user’s codebase, supporting immediate monitoring of LLM calls and agentic systems. The service is aimed at developers and teams building and operating AI applications, from those exploring their first AI app to organizations running complex production systems. It offers several pricing tiers: a free plan for initial exploration and debugging (with limits on traces, workspaces, and data retention), and paid plans scaling up to support higher volumes, more workspaces, longer retention, advanced analytics, collaboration, alerts, SSO, API access, and dedicated support. All plans include features for observability, evaluation, and optimization from the outset.
As an AI evaluation and observability platform, Tracium is positioned for developers and teams seeking comprehensive, real-time monitoring and analytics for their AI agents and workflows. Its emphasis on simplicity, rapid integration, and multi-tenant analytics makes it suitable for a range of AI development and production environments.
In the LLM eval & observability space, tracium takes a focused approach. It focuses on monitoring and debugging AI agents' performance, costs, and errors with minimal setup. It is built as a B2B product for AI developers. A free plan is available. tracium is available on the web and the command line.
It is developed by Tracium.ai, and it first shipped in 2025. Key capabilities include AI agent tracking, cost monitoring, and error tracing.
Summary written by a language model from the project’s public pages.
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