Best AI Observability Tools

Grafana Labs delivers the leading AI-powered observability platform, built around Grafana—the world’s most widely adopted open source technology for dashboards and visualization. Recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Observability Platforms (3x) and furthest in Completeness of Vision (2025, 2026), Grafana Labs supports more than 25 million users and thousands of organizations, from startups to the Fortune 500. Grafana Cloud is the open observability cloud, built on open source, open standards, and open ecosystems. Powered by the LGTM stack—Grafana (visualization), Mimir (metrics), Loki (logs) & Tempo (traces)—it unifies telemetry in one platform for full-stack visibility across applications, infrastructure, and digital experiences. With the AI-powered Grafana Assistant and Adaptive Telemetry suite, teams detect and resolve issues faster, reduce wasteful telemetry spend, and gain real-time insights to ensure reliability. Native OTel support and 100s of integrations mean you can plug in existing tools & data sources.

There are an estimated 25 million engineers in the world across dozens of distinct functions. As every company becomes a software company, engineers are using New Relic to gather real-time insights and trending data about the performance of their software so they can be more resilient and deliver exceptional customer experiences. Only New Relic provides an all-in-one platform that is built and sold as a unified experience. With New Relic, customers get access to a secure telemetry cloud for all metrics, events, logs, and traces; powerful full-stack analysis tools; and simple, transparent usage-based pricing with only 2 key metrics. New Relic has also curated one of the industry’s largest ecosystems of open source integrations, making it easy for every engineer to get started with observability and use New Relic alongside their other favorite applications.

Cloudflare is the foundation for your infrastructure, applications, and teams. Cloudflare secures and ensures the reliability of your external-facing resources such as websites, APIs, and applications. It protects your internal resources such as behind-the-firewall applications, teams, and devices. And it is your platform for developing globally scalable applications. Your website, APIs, and applications are your key channels for doing business with your customers and suppliers. As more and more shift online, ensuring these resources are secure, performant and reliable is a business imperative. Cloudflare for Infrastructure is a complete solution to enable this for anything connected to the Internet. Behind-the-firewall applications and devices are foundational to the work of your internal teams. The recent surge in remote work is testing the limits of many organizations’ VPN and other hardware solutions.

Trusys.ai is a unified AI assurance platform that helps organizations evaluate, secure, monitor, and govern artificial intelligence systems across their full lifecycle, from early testing to production deployment. It offers a suite of tools: TRU SCOUT for automated security and compliance scanning against global standards and adversarial vulnerabilities, TRU EVAL for comprehensive functional evaluation of AI applications (text, voice, image, and agent) assessing accuracy, bias, and safety, and TRU PULSE for real-time production monitoring with alerts for drift, performance degradation, policy violations, and anomalies. It provides end-to-end observability and performance tracking, enabling teams to catch unreliable output, compliance gaps, and production issues early. Trusys supports model-agnostic evaluation with a no-code, intuitive interface and integrates human-in-the-loop reviews and custom scoring metrics to blend expert judgment with automated metrics.

The Dynatrace software intelligence platform. Transform faster with unparalleled observability, automation, and intelligence in one platform. Leave the bag of tools behind, with one platform to automate your dynamic multicloud and align multiple teams. Spark collaboration between biz, dev, and ops with the broadest set of purpose-built use cases in one place. Harness and unify even the most complex dynamic multiclouds, with out-of-the box support for all major cloud platforms and technologies. Get a broader view of your environment. One that includes metrics, logs, and traces, as well as a full topological model with distributed tracing, code-level detail, entity relationships, and even user experience and behavioral data – all in context. Weave Dynatrace’s open API into your existing ecosystem to drive automation in everything from development and releases to cloud ops and business processes.

Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.

Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export data

Taam Cloud is a powerful AI API platform designed to help businesses and developers seamlessly integrate AI into their applications. With enterprise-grade security, high-performance infrastructure, and a developer-friendly approach, Taam Cloud simplifies AI adoption and scalability. Taam Cloud is an AI API platform that provides seamless integration of over 200 powerful AI models into applications, offering scalable solutions for both startups and enterprises. With products like the AI Gateway, Observability tools, and AI Agents, Taam Cloud enables users to log, trace, and monitor key AI metrics while routing requests to various models with one fast API. The platform also features an AI Playground for testing models in a sandbox environment, making it easier for developers to experiment and deploy AI-powered solutions. Taam Cloud is designed to offer enterprise-grade security and compliance, ensuring businesses can trust it for secure AI operations.

Track costs, usage, and latency for GPT applications with one line of code. Trusted by leading companies building with OpenAI. We will support Anthropic, Cohere, Google AI, and more coming soon. Stay on top of your costs, usage, and latency. Integrate models like GPT-4 with Helicone to track API requests and visualize results. Get an overview of your application with an in-built dashboard, tailor made for generative AI applications. View all of your requests in one place. Filter by time, users, and custom properties. Track spending on each model, user, or conversation. Use this data to optimize your API usage and reduce costs. Cache requests to save on latency and money, proactively track errors in your application, handle rate limits and reliability concerns with Helicone.

Dash0 is an OpenTelemetry-native observability platform for developers and SRE teams. Metrics, logs, traces, and resources sit in one place, linked by OpenTelemetry semantic conventions, so you move from a slow trace to the logs around it without switching tools. Telemetry arrives over OTLP. No proprietary agent, nothing to re-instrument, and your data stays portable. Dash0 ingests Prometheus metrics alongside OpenTelemetry, supports PromQL, and imports existing Prometheus alerting rules and Grafana dashboards. A Kubernetes operator handles collection across clusters. Dashboards are built on Perses and defined as code, so they live in Git alongside your infrastructure. Log AI infers severity, extracts patterns, and groups records, making unstructured third-party logs searchable. Trace triage uses the SIFT framework to narrow a failing request toward a cause. Spend is visible in-product: see which services and log volumes drive cost, and cut them at the source.

Athina is a collaborative AI development platform that enables teams to build, test, and monitor AI applications efficiently. It offers features such as prompt management, evaluation tools, dataset handling, and observability, all designed to streamline the development of reliable AI systems. Athina supports integration with various models and services, including custom models, and ensures data privacy through fine-grained access controls and self-hosted deployment options. The platform is SOC-2 Type 2 compliant, providing a secure environment for AI development. Athina's user-friendly interface allows both technical and non-technical team members to collaborate effectively, accelerating the deployment of AI features.

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.

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.

Overseer AI is a platform designed to ensure AI-generated content is safe, accurate, and aligned with user-defined policies. It offers compliance enforcement by automating adherence to regulatory standards through custom policy rules, real-time content moderation to block harmful, toxic, or biased outputs from AI, debugging AI outputs by testing and monitoring responses against custom safety policies, policy-driven AI governance by applying centralized safety rules across all AI interactions, and trust-building for AI by guaranteeing safe, accurate, and brand-compliant outputs. The platform caters to various industries, including healthcare, finance, legal technology, customer support, education technology, and ecommerce & retail, providing tailored solutions to ensure AI responses align with industry-specific regulations and standards. Developers can access comprehensive guides and API references to integrate Overseer AI into their applications.

Prompteus is a platform designed to simplify the creation, management, and scaling of AI workflows, enabling users to build production-ready AI systems in minutes. It offers a visual editor to design workflows, which can then be deployed as secure, standalone APIs, eliminating the need for backend management. Prompteus supports multi-LLM integration, allowing users to connect to various large language models with dynamic switching and optimized costs. It also provides features like request-level logging for performance tracking, smarter caching to reduce latency and save on costs, and seamless integration into existing applications via simple APIs. Prompteus is serverless, scalable, and secure by default, ensuring efficient AI operation across different traffic volumes without infrastructure concerns. Prompteus helps users reduce AI provider costs by up to 40% through semantic caching and detailed analytics on usage patterns.

Vivgrid is a development platform for AI agents that emphasizes observability, debugging, safety, and global deployment infrastructure. It gives you full visibility into agent behavior, logging prompts, memory fetches, tool usage, and reasoning chains, letting developers trace where things break or deviate. You can test, evaluate, and enforce safety policies (like refusal rules or filters), and incorporate human-in-the-loop checks before going live. Vivgrid supports the orchestration of multi-agent systems with stateful memory, routing tasks dynamically across agent workflows. On the deployment side, it operates a globally distributed inference network to ensure low-latency (sub-50 ms) execution and exposes metrics like latency, cost, and usage in real time. It aims to simplify shipping resilient AI systems by combining debugging, evaluation, safety, and deployment into one stack, so you're not stitching together observability, infrastructure, and orchestration.

Foxglove is a visualization, observability, and data management platform purpose-built for robotics and embodied AI development that centralizes and simplifies working with large, multimodal temporal datasets, including time series, sensor logs, imagery, lidar/point clouds, geospatial maps, and more, in a single, integrated workspace. It enables engineers to record, import, organize, stream, and visualize both live and recorded data from robots using intuitive, customizable dashboards with interactive panels for 3D scenes, plots, raw messages, images, and maps, helping users understand how robots sense, think, and act. Foxglove supports real-time connections to systems like ROS and ROS 2 via bridges and web sockets, enables cross-platform workflows (desktop app for Linux, Windows, and macOS), and facilitates rapid analysis, debugging, and performance optimization by synchronizing diverse data sources in time and space.

Scorable is an AI evaluation and monitoring platform designed to help developers measure, control, and improve the behavior of applications built with large language models. It enables teams to create customized automated evaluators, sometimes referred to as AI “judges”, that assess how an AI system responds to users and whether its outputs meet defined quality standards such as accuracy, relevance, helpfulness, tone, and policy compliance. Developers can describe what they want to measure in plain language, and the platform generates a tailored evaluation stack that tests AI outputs against context-specific criteria rather than generic benchmarks. These evaluators can be embedded directly into application code, allowing AI systems such as chatbots, retrieval-augmented generation (RAG) systems, or autonomous agents to be continuously monitored in production environments.

Openlayer is the AI governance and observability platform that accelerates the evaluation and observability of agentic systems through 100+ automated tests and real-time guardrails that prevent prompt injections, PII leakage, bias, toxicity, and hallucinations, powering secure enterprise innovation. Designed to support both traditional ML and GenAI systems, Openlayer helps teams seamlessly handle everything from data-quality detection to automating comprehensive model evaluations, with full traceability across RAG, agents, and complex multi-step workflows. Trusted by Fortune 500 companies from early experimentation through production deployment and automated governance capabilities (NIST, EU AI Act, etc.)., Openlayer enables safe, reliable, and responsible AI operations.

Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!

Foresee problems before they occur with an Azure AI anomaly detection service. Easily embed time-series anomaly detection capabilities into your apps to help users identify problems quickly. AI Anomaly Detector ingests time-series data of all types and selects the best anomaly detection algorithm for your data to ensure high accuracy. Detect spikes, dips, deviations from cyclic patterns, and trend changes through both univariate and multivariate APIs. Customize the service to detect any level of anomaly. Deploy the anomaly detection service where you need it, in the cloud or at the intelligent edge. A powerful inference engine assesses your time-series dataset and automatically selects the right anomaly detection algorithm to maximize accuracy for your scenario. Automatic detection eliminates the need for labeled training data to help you save time and stay focused on fixing problems as soon as they surface.

Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security.

Track model performance to detect and react to data drift, improving model accuracy for better business outcomes. Build trust, ensure compliance, and drive more actionable ML outcomes with Arthur’s explainability and transparency APIs. Proactively monitor for bias, track model outcomes against custom bias metrics, and improve the fairness of your models. See how each model treats different population groups, proactively 
identify bias, and use Arthur's proprietary bias mitigation techniques. Arthur scales up and down to ingest up to 1MM transactions 
per second and deliver insights quickly. Actions can only be performed by authorized users. Individual teams/departments can have isolated environments with specific access control policies. Data is immutable once ingested, which prevents manipulation of metrics/insights.