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Coralogix Launches AI Center

Coralogix launched AI Center, which empowers organizations with real-time visibility into all of their AI applications. 

By delivering comprehensive, real-time insights into AI performance, quality, security, and governance within a single platform, the AI Center empowers businesses to accelerate AI adoption and manage AI agents with confidence.

Coralogix tackles this issue by observing with customizable evaluators that address the “grey areas,” i.e. when AI appears to perform correctly, but has issues related to its responses. 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 bad actor is trying to breach the chatbot to steal customer data.

With this addition, Coralogix is now the first cross-stack observability platform, transforming how businesses analyze their software, security, and AI systems. The company’s unique ability to analyze data in real-time as it’s ingested provides businesses with real-time monitoring, advanced analytics, and incident management, all while significantly reducing costs and time-to-insight.

“AI is not just another technology layer; it’s a distinct stack with its own complexities and risks,” said Ariel Assaraf, CEO of Coralogix. “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. This launch represents a significant step forward in our mission to provide the most advanced cross-stack observability platform imaginable.”

In December 2024, Coralogix acquired Aporia, a leading provider of AI observability and guardrails. That acquisition fueled the rapid development of advanced AI solutions, culminating in today’s launch.

Coralogix’s AI Center Provides:

  • AI Evaluation Engine: Allows users to evaluate AI applications for quality, correctness, security and compliance. Moreover, they can tailor specialized evaluators for each AI use case. The evaluators actively assess each interaction, scanning every prompt and response for potential risks or quality issues.
  • AI-SPM (Security Posture Management): Provides real-time, dedicated monitoring of the security and performance of AI agents across an organization. Its dashboards highlight risks such as prompt injections, data leaks, and PII leakage, allowing teams to pinpoint and address breaches or security risks.
  • Complete User Journey & Cost Tracking: Provides full visibility into user interactions, from conversation histories and logins to token usage. This granular tracking enables teams to pinpoint suspicious resource consumption, detect cost harvesting attempts, and optimize budgets without compromising performance.
  • Performance Metrics: Delivers in-depth insights into AI agent performance. It detects issues like poor response accuracy, latency spikes, and malicious user inputs, enabling teams to resolve underperforming agents before they impact the user experience. By focusing on AI-specific metrics, organizations can ensure a seamless, high-quality AI environment.

“The launch of our AI Center unlocks a significant barrier faced by many AI teams - crossing the chasm from pilot to production,” commented Liran Hason, VP of AI, Coralogix and previously CEO of Aporia. “Having a centralized place to observe and manage all your AI applications for performance, quality and security is the key missing piece to launching AI apps safely.”

“Acquiring Aporia enabled us to rapidly deliver real-time AI observability and establish our new AI Research Center,” said Yoni Farin, CTO and Co-founder of Coralogix. “This expansion goes beyond observability; we’re investing in top-tier talent to build the next generation of AI-driven solutions for our customers worldwide.”

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Coralogix Launches AI Center

Coralogix launched AI Center, which empowers organizations with real-time visibility into all of their AI applications. 

By delivering comprehensive, real-time insights into AI performance, quality, security, and governance within a single platform, the AI Center empowers businesses to accelerate AI adoption and manage AI agents with confidence.

Coralogix tackles this issue by observing with customizable evaluators that address the “grey areas,” i.e. when AI appears to perform correctly, but has issues related to its responses. 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 bad actor is trying to breach the chatbot to steal customer data.

With this addition, Coralogix is now the first cross-stack observability platform, transforming how businesses analyze their software, security, and AI systems. The company’s unique ability to analyze data in real-time as it’s ingested provides businesses with real-time monitoring, advanced analytics, and incident management, all while significantly reducing costs and time-to-insight.

“AI is not just another technology layer; it’s a distinct stack with its own complexities and risks,” said Ariel Assaraf, CEO of Coralogix. “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. This launch represents a significant step forward in our mission to provide the most advanced cross-stack observability platform imaginable.”

In December 2024, Coralogix acquired Aporia, a leading provider of AI observability and guardrails. That acquisition fueled the rapid development of advanced AI solutions, culminating in today’s launch.

Coralogix’s AI Center Provides:

  • AI Evaluation Engine: Allows users to evaluate AI applications for quality, correctness, security and compliance. Moreover, they can tailor specialized evaluators for each AI use case. The evaluators actively assess each interaction, scanning every prompt and response for potential risks or quality issues.
  • AI-SPM (Security Posture Management): Provides real-time, dedicated monitoring of the security and performance of AI agents across an organization. Its dashboards highlight risks such as prompt injections, data leaks, and PII leakage, allowing teams to pinpoint and address breaches or security risks.
  • Complete User Journey & Cost Tracking: Provides full visibility into user interactions, from conversation histories and logins to token usage. This granular tracking enables teams to pinpoint suspicious resource consumption, detect cost harvesting attempts, and optimize budgets without compromising performance.
  • Performance Metrics: Delivers in-depth insights into AI agent performance. It detects issues like poor response accuracy, latency spikes, and malicious user inputs, enabling teams to resolve underperforming agents before they impact the user experience. By focusing on AI-specific metrics, organizations can ensure a seamless, high-quality AI environment.

“The launch of our AI Center unlocks a significant barrier faced by many AI teams - crossing the chasm from pilot to production,” commented Liran Hason, VP of AI, Coralogix and previously CEO of Aporia. “Having a centralized place to observe and manage all your AI applications for performance, quality and security is the key missing piece to launching AI apps safely.”

“Acquiring Aporia enabled us to rapidly deliver real-time AI observability and establish our new AI Research Center,” said Yoni Farin, CTO and Co-founder of Coralogix. “This expansion goes beyond observability; we’re investing in top-tier talent to build the next generation of AI-driven solutions for our customers worldwide.”

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...