List of the Top Agentic AI Platforms for OpenTelemetry in 2026

Reviews and comparisons of the top Agentic AI platforms with an OpenTelemetry integration


Below is a list of Agentic AI platforms that integrates with OpenTelemetry. Use the filters above to refine your search for Agentic AI platforms that is compatible with OpenTelemetry. The list below displays Agentic AI platforms products that have a native integration with OpenTelemetry.
  • 1
    Plano Reviews & Ratings

    Plano

    Katanemo Labs

    Streamline AI application delivery with seamless infrastructure management.
    Plano is a comprehensive AI delivery infrastructure platform designed to simplify the development, deployment, and operation of agentic applications. Built as an AI-native data plane and proxy layer, the platform handles the complex infrastructure components required to support modern AI agents at scale. Developers can leverage Plano to manage agent orchestration, intelligent model routing, observability, security controls, context engineering, and policy enforcement through a centralized architecture. The platform enables seamless integration with more than one language model provider through a unified API, reducing the complexity of multi-model deployments. Detailed tracing and monitoring capabilities provide deep insights into agent interactions, helping teams troubleshoot issues, improve reliability, and support reinforcement learning workflows. Plano’s architecture allows developers to continue using their preferred programming languages, frameworks, and development tools without introducing restrictive dependencies. Built-in guardrails help detect and mitigate risks such as jailbreak attempts while enforcing organizational policies across applications. The platform also supports reusable context engineering filters that improve agent responses and operational consistency. Organizations operating in regulated industries can deploy Plano on-premises to maintain greater control over sensitive data and infrastructure. Its configuration-driven approach simplifies deployment by allowing teams to define agent behavior, model preferences, and integrations through a streamlined setup process. By handling the underlying plumbing of AI systems, Plano empowers organizations to focus on innovation, accelerate development cycles, and deliver production-ready AI agents with greater confidence.
  • 2
    Golf Reviews & Ratings

    Golf

    Golf

    Streamline AI-agent infrastructure with secure, scalable simplicity.
    GolfMCP is an open-source framework designed to streamline the creation and deployment of production-ready Model Context Protocol (MCP) servers, enabling organizations to build a secure and scalable environment for AI agents without the burden of boilerplate code. By allowing developers to easily define tools, prompts, and resources with simple Python files, GolfMCP handles vital operations such as routing, authentication, telemetry, and observability, which allows users to focus on the essential logic instead of the underlying infrastructure. The platform supports advanced authentication methods like JWT, OAuth Server, and API keys, along with automated telemetry and a file-based structure that eliminates the need for decorators or manual schema setups. It also provides built-in tools for interacting with large language models (LLMs), comprehensive error logging, OpenTelemetry integration, and deployment utilities, including a command-line interface that offers commands for initializing, building, and running projects. Additionally, GolfMCP features the Golf Firewall, a sturdy security layer specifically designed for MCP servers that implements strict token validation to bolster the security framework. This extensive array of features guarantees that developers have all the necessary tools at their disposal to create effective AI-driven applications, paving the way for innovation and efficiency in their projects. With GolfMCP, organizations can confidently advance their AI initiatives with a robust and user-friendly development environment.
  • 3
    Amazon Bedrock AgentCore Reviews & Ratings

    Amazon Bedrock AgentCore

    Amazon

    Empower AI agents with seamless integration and robust scalability.
    Amazon Bedrock's AgentCore provides a secure framework for the scalable deployment and management of sophisticated AI agents, equipped with infrastructure specifically tailored for dynamic workloads, advanced tools for agent optimization, and essential controls for practical applications. It supports any framework and foundation model, both within and outside of Amazon Bedrock, effectively removing the need for specialized infrastructure. AgentCore guarantees complete isolation of sessions and boasts industry-leading performance for extended workloads lasting up to eight hours, integrating effortlessly with existing identity providers to facilitate smooth authentication and permission oversight. Moreover, it employs a gateway to transform APIs into ready-to-use tools for agents, requiring minimal coding, while its built-in memory retains context throughout user interactions. Additionally, agents are provided with a secure browsing environment that allows them to undertake complex web tasks, along with a sandboxed code interpreter suitable for operations like generating visualizations, thereby enriching their capabilities. This comprehensive suite of features not only simplifies the development process but also empowers organizations to effectively harness the potential of AI technology, ultimately leading to greater innovation and efficiency in their operations. In essence, AgentCore represents a significant leap forward in enabling businesses to adapt and thrive in an increasingly digital landscape.
  • 4
    bitdrift Reviews & Ratings

    bitdrift

    bitdrift

    Empower developers with seamless, real-time mobile app insights.
    Bitdrift stands out as a groundbreaking mobile observability tool crafted to equip developers with robust debugging functionalities for their production applications, transcending the limitations of traditional telemetry systems. By utilizing a fixed-resource Ring Buffer, it captures a wealth of device-side data, allowing teams to collect an abundance of telemetry information while ensuring that only the most relevant data is retained and scrutinized. The platform boasts integrated monitoring capabilities that unveil essential metrics, including network latency, API success rates, resource consumption, crashes, freezes, and a variety of other indicators that reflect the application's health across the entire fleet. Moreover, developers have the flexibility to introduce new targeting criteria, workflows, and alterations to data collection in real time, which negates the necessity of deploying a new version of the app or awaiting app store approvals. In addition, the Session Replay feature delivers a privacy-conscious and intricately detailed reconstruction of user sessions, correlating them with logs and additional telemetry to illuminate both user interactions and the app's internal processes, ultimately contributing to an elevated quality of the application. Collectively, these capabilities empower teams to promptly address issues and perpetually enhance their applications, fostering an agile development environment that adapts to user needs. This advanced approach to mobile observability marks a significant shift in how developers can monitor and optimize their applications in the ever-evolving tech landscape.
  • 5
    Flue Reviews & Ratings

    Flue

    Flue

    "Craft intelligent, resilient AI agents with seamless programming."
    Flue represents a cutting-edge framework aimed at building resilient AI agents within a customizable TypeScript setting. Created by the team behind Astro, it features a React-like hooks API that supports the development of various agent functionalities such as persistent state management, lifecycle events, and a variety of models and tools, all seamlessly integrated into the coding environment. These agents not only maintain their state but can also be accessed through HTTP protocols, ensuring context is preserved during interactions while they adapt their capabilities as tasks change. With Flue, every session is meticulously recorded in a dependable stream, facilitating task recovery even after unexpected crashes or restarts, which allows for a smooth continuation of interrupted sessions without requiring clients to start over. Developers have the option to run agents locally, utilize continuous integration, connect them with their own backend infrastructures, or manage them through services like Cloudflare Workflows and Inngest. The framework includes secure sandboxes where agents can carry out commands, alter files, and engage in productive tasks, while built-in tools provide connections to numerous APIs and data sources. Additionally, Flue is powered by Pi and supports various LLM providers, giving teams the flexibility to choose models that align with their specific requirements. This innovative framework ultimately equips developers with the means to create adaptable AI agents capable of responding to shifting demands and environments, enhancing their overall functionality and efficiency. By streamlining the process of agent creation, Flue not only simplifies the development journey but also opens up new possibilities for AI applications across diverse industries.
  • Previous
  • You're on page 1
  • Next