University of Kwazulu-Natal

The Best Ai Observability Tools In 2025 Coralogix

Bonisiwe Shabane
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the best ai observability tools in 2025 coralogix

<img decoding="async" src="/wp-content/uploads/2025/06/Group-2147255857.svg" alt="" /> The new standard of observability is here. Discover Olly, the industry’s first Autonomous Observability Agent. → KubeCon + CloudNativeCon North America 2025 In 2025, AI isn’t just an add-on—it’s the engine powering everything from personalized customer experiences to mission-critical enterprise operations. Modern systems generate 5–10 terabytes of telemetry data daily as they juggle intricate cloud-native architectures, microservices, and cutting-edge generative AI workloads.

This sheer volume and complexity have pushed traditional monitoring to its limits, leaving a critical gap in proactive management. Imagine having a panoramic view over your entire AI ecosystem—a real-time, unified dashboard that not only aggregates logs, metrics, and traces but also detects subtle anomalies before they evolve into costly disruptions. AI observability is the process of monitoring and understanding AI systems in production to ensure they operate effectively, securely, and cost-efficiently. The best tools in 2025 focus on real-time monitoring, security, and cost management for cloud-native AI deployments. Here's a quick overview of the top five tools: Each tool addresses unique needs, from managing costs to ensuring security and compliance.

Below is a comparison to help you choose the right one for your organization. Coralogix brings a sharp focus to the performance, security, and cost clarity of scalable, cloud-native AI systems. With Coralogix AI Observability, you get real-time insights into how AI systems are performing, uncover security threats, and manage operational costs effectively. The platform excels at providing detailed tracing and analytics for AI applications, tracking key metrics like errors, token usage, costs, and response times - all without disrupting user experiences in generative AI environments. Coralogix offers instant visibility into AI operations through specialized dashboards. These dashboards highlight critical metrics like latency, error rates, and token consumption across different models and applications.

This allows teams to spot performance trends and address bottlenecks before they impact users. On top of that, the platform’s risk assessment and metadata tracking tools pinpoint abusive behaviors and potential data leaks, giving security teams actionable insights. One standout feature is its ability to scan GitHub repositories to identify where generative AI is being used within an organization. This helps security teams maintain control and minimize risks tied to AI deployments. The platform’s real-time visibility works seamlessly across various deployment environments, ensuring comprehensive oversight. AI News is part of the TechForge Publications series

AI systems aren’t experimental anymore, they’re embedded in everyday decisions that affect millions. Yet as these models stretch into important spaces like real-time supply chain routing, medical diagnostics, and financial markets, something as simple as a stealthy data shift or an undetected anomaly can flip confident automation... This isn’t just a problem for data scientists or machine learning engineers. Today, product managers, compliance officers, and business leaders are realising that AI’s value doesn’t just hinge on building a high-performing model, but on deeply understanding how, why, and when these models behave the way... Enter AI observability, a discipline that’s no longer an optional add-on, but a daily reality for teams committed to reliable, defensible, and scalable AI-driven products. Logz.io stands out in the AI observability landscape by providing an open, cloud-native platform tailored for the complexities of modern ML and AI systems.

Its architecture fuses telemetry, logs, metrics, and traces into one actionable interface, empowering teams to visualize and analyse every stage of the AI lifecycle. AI observability provides end-to-end visibility into agent behavior, spanning prompts, tool calls, retrievals, and multi-turn sessions. In 2025, teams rely on observability to maintain AI reliability across complex stacks and non-deterministic workflows. Platforms that support distributed tracing, online evaluations, and cross-team collaboration help catch regressions early and ship trustworthy AI faster. Non-determinism: LLMs vary run-to-run, making reproducibility challenging. Distributed tracing across traces, spans, generations, tool calls, retrievals, and sessions turns opaque behavior into explainable execution paths that engineering teams can debug systematically.

Production reliability: Observability catches regressions early through online evaluations, alerts, and dashboards that track latency, error rate, and quality scores. Weekly reports and saved views help teams identify trends before they impact end users. Cost and performance control: Token usage and per-trace cost attribution surface expensive prompts, slow tools, and inefficient RAG implementations. Optimizing with this visibility reduces spend without sacrificing quality, a critical consideration as AI applications scale. Tooling and integrations: OTEL/OTLP support enables teams to route the same traces to Maxim's observability platform and existing collectors like Snowflake or New Relic for unified operations, eliminating dual instrumentation overhead. Unite.AI is committed to rigorous editorial standards.

We may receive compensation when you click on links to products we review. Please view our affiliate disclosure. The artificial intelligence observability market is experiencing explosive growth, projected to reach $10.7 billion by 2033 with a compound annual growth rate of 22.5%. As AI adoption accelerates—with 78% of organizations now using AI in at least one business function, up from 55% just two years ago—effective monitoring has become mission-critical for ensuring reliability, transparency, and compliance. Organizations deploying AI at scale face unique challenges including data drift, concept drift, and emergent behaviors that traditional monitoring tools weren’t designed to handle. Modern AI observability platforms combine the ability to track model performance with specialized features like bias detection, explainability metrics, and continuous validation against ground truth data.

This comprehensive guide explores the most powerful AI observability platforms available today, providing detailed information on capabilities, pricing, pros and cons, and recent developments to help you make an informed decision for your organization’s... Founded in 2020, Arize AI has secured $131 million in funding, including a recent $70 million Series C round in February 2025. The company serves high-profile clients like Uber, DoorDash, and the U.S. Navy. Their platform provides end-to-end AI visibility with OpenTelemetry instrumentation, offering continuous evaluation capabilities with LLM-as-a-Judge functionality. Smarter, faster, safer AI begins with full visibility.

Coralogix’s AI Center provides the most advanced AI observability tools and dashboards, so you are fully in the know. Catch hallucinations, incorrect responses and system errors before they break the user experience and cause mistrust. Monitor how each agent behaves across prompts, responses, workloads and model types to spot errors or sudden degradation. Surface inefficient prompts, token overuse, unexpected usage spikes, or cost harvesting attempts in real-time. Our one-of-a-kind Evaluation Engine gives you complete control: assign out-of-the-box or custom evaluators, such as for hallucinations, PII leaks, relevance, toxicity, and more, to every AI agent. Each message is scored in real time, so you can spot where the AI or user might be out of line.

Full-stack observability platform company Coralogix Ltd. today launched AI Center, a real-time observability platform designed to provide comprehensive insights into AI performance, quality, security and governance. AI Center seeks to assist with the growing issue where as enterprises adopt AI, they require rigorous oversight, as inadequate management can lead to unforeseen or inequitable outcomes. Coralogix argues that existing AI observability approaches fall short by focusing on performance versus other attributes that impact effective usage. Coralogix takes on observability problems with customizable evaluators that tackle the “gray areas,” such as when AI appears to perform correctly but has issues related to its responses. Differing from other vendors, Coralogix reviews the content of the user and the AI to determine whether, for example, there is a chance that an exchange contains toxicity, the AI is hallucinating, or a...

“AI is not just another technology layer; it’s a distinct stack with its own complexities and risks,” explained Chief Executive Ariel Assaraf. “Our AI Center delivers real-time transparency into every aspect of that stack, ensuring organizations can monitor, troubleshoot and secure their AI initiatives before minor errors become major crises.” AI Center strengthens organizations with an AI Evaluation Engine to assess the quality, correctness, security and compliance of AI applications. The service allows users to create specialized evaluators for different AI use cases, actively scanning prompts and responses for potential risks or quality issues. Enterprise software provider Coralogix recently pulled in $115 million in a Series E funding round that brings its valuation to over $1 billion. The company will use the capital to accelerate the rollout of Olly, its new AI agent designed for observability.

Olly works to make deep observability data accessible across an organization, including both technical and non-technical teams. The tool can determine the root cause of a technical failure within minutes, and it provides insights in plain language to help teams make the next move. The agent’s release marks Coralogix’s official expansion into the AI space, and it follows several other moves the company announced in 2025. Coralogix recently acquired Aporia, a solution for AI observability and guardrails, and it launched the Coralogix AI Center to offer real-time observability for AI applications on a unified platform. Related ResourcesTech & Startup Jobs in Boston

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