Best Telemetry Software for OpenAI

Compare the Top Telemetry Software that integrates with OpenAI as of July 2025

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This a list of Telemetry software that integrates with OpenAI. Use the filters on the left to add additional filters for products that have integrations with OpenAI. View the products that work with OpenAI in the table below.

What is Telemetry Software for OpenAI?

Telemetry software is designed to collect, transmit, and analyze data from remote or distributed systems in real time. It allows organizations to monitor the performance, health, and behavior of various devices, machines, or applications from a central location. The software gathers data such as system metrics, error logs, or user interactions, and sends it to a centralized database or server for analysis. This data is then used to identify issues, optimize performance, or predict future problems. Telemetry software is widely used in industries like aerospace, automotive, telecommunications, and IT infrastructure for proactive maintenance and decision-making. Compare and read user reviews of the best Telemetry software for OpenAI currently available using the table below. This list is updated regularly.

1

Observe

Observe

Observe – the AI-powered observability company – is reinventing how businesses detect anomalies, troubleshoot applications, and resolve incidents to deliver exceptional customer experiences. Only Observe eliminates silos of logs, metrics, and traces by storing all data in a single, cost-efficient data lake, analyzing all telemetry data using a single language, and providing access through a single, consistent, user interface. Observe’s AI-Powered Observability enables companies to resolve software incidents three times faster at one-third the cost. Customers such as Capital One, Dialpad AI, Top Golf and more trust Observe to turn their data into actionable insights.

Starting Price: $0.35 Per GiB

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2

OpenLIT

OpenLIT

OpenLIT is an OpenTelemetry-native application observability tool. It's designed to make the integration process of observability into AI projects with just a single line of code. Whether you're working with popular LLM libraries such as OpenAI and HuggingFace. OpenLIT's native support makes adding it to your projects feel effortless and intuitive. Analyze LLM and GPU performance, and costs to achieve maximum efficiency and scalability. Streams data to let you visualize your data and make quick decisions and modifications. Ensures that data is processed quickly without affecting the performance of your application. OpenLIT UI helps you explore LLM costs, token consumption, performance indicators, and user interactions in a straightforward interface. Connect to popular observability systems with ease, including Datadog and Grafana Cloud, to export data automatically. OpenLIT ensures your applications are monitored seamlessly.

Starting Price: Free

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3

Langtrace

Langtrace

Langtrace is an open source observability tool that collects and analyzes traces and metrics to help you improve your LLM apps. Langtrace ensures the highest level of security. Our cloud platform is SOC 2 Type II certified, ensuring top-tier protection for your data. Supports popular LLMs, frameworks, and vector databases. Langtrace can be self-hosted and supports OpenTelemetry standard traces, which can be ingested by any observability tool of your choice, resulting in no vendor lock-in. Get visibility and insights into your entire ML pipeline, whether it is a RAG or a fine-tuned model with traces and logs that cut across the framework, vectorDB, and LLM requests. Annotate and create golden datasets with traced LLM interactions, and use them to continuously test and enhance your AI applications. Langtrace includes built-in heuristic, statistical, and model-based evaluations to support this process.

Starting Price: Free

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4

Arize Phoenix

Arize AI

Phoenix is an open-source observability library designed for experimentation, evaluation, and troubleshooting. It allows AI engineers and data scientists to quickly visualize their data, evaluate performance, track down issues, and export data to improve. Phoenix is built by Arize AI, the company behind the industry-leading AI observability platform, and a set of core contributors. Phoenix works with OpenTelemetry and OpenInference instrumentation. The main Phoenix package is arize-phoenix. We offer several helper packages for specific use cases. Our semantic layer is to add LLM telemetry to OpenTelemetry. Automatically instrumenting popular packages. Phoenix's open-source library supports tracing for AI applications, via manual instrumentation or through integrations with LlamaIndex, Langchain, OpenAI, and others. LLM tracing records the paths taken by requests as they propagate through multiple steps or components of an LLM application.

Starting Price: Free

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5

Logfire

Pydantic

Pydantic Logfire is an observability platform designed to simplify monitoring for Python applications by transforming logs into actionable insights. It provides performance insights, tracing, and visibility into application behavior, including request headers, body, and the full trace of execution. Pydantic Logfire integrates with popular libraries and is built on top of OpenTelemetry, making it easier to use while retaining the flexibility of OpenTelemetry's features. Developers can instrument their apps with structured data, and query-ready Python objects, and gain real-time insights through visualizations, dashboards, and alerts. Logfire also supports manual tracing, context logging, and exception capturing, providing a modern logging interface. It is tailored for developers seeking a streamlined, effective observability tool with out-of-the-box integrations and ease of use.

Starting Price: $2 per month

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