Coralogix

What Coralogix does

Coralogix is a modern observability platform that provides real-time insights across systems, security, and AI workloads. It processes data in-stream and stores it directly in the customer’s cloud, delivering full data fidelity without indexing or sampling, which reduces costs. The platform allows teams to monitor, troubleshoot, and make decisions using 100% of their telemetry data. Coralogix is also the creator of Olly, an agentic AI observability assistant that enables users to ask plain-language questions for instant understanding of production environments, making complex telemetry accessible without writing queries or building dashboards. The platform unifies logs, metrics, traces, and security data, offering a unique index-free architecture for scalability and cost efficiency. It supports infinite data retention by storing telemetry in the customer's cloud in open formats, allowing for remote, index-free querying. Coralogix is built for teams needing observability to drive clarity, action, and scale, serving over 4,000 customers worldwide.

Products

• OllyAn agentic AI observability assistant that allows users to ask plain-language questions and instantly understand what’s happening in production, making complex telemetry accessible without writing queries or building dashboards. It serves as a conversational investigator.
• Model Context Protocol (MCP)An ecosystem connector that surfaces Coralogix insights directly in Slack, PagerDuty, or an IDE. It is an open protocol and server that enables external AI agents to access and analyze Coralogix observability data (logs, metrics, traces) via a remote streamable HTTP transport-powered interface, supporting AI-native troubleshooting and root cause analysis.
• Command-line interface (CLI)An automation engine that allows scripting investigations, piping results into runbooks, or integrating with CI/CD, making AI programmable infrastructure.
• Cost OptimizerDelivers instant analysis for critical logs while offloading low-value data to customer storage, aiming to reduce costs while maintaining visibility.
• AI Hallucination EvaluatorA real-time AI evaluation engine designed to prevent AI hallucinations by confirming context relevance, ensuring answers derive from context, and verifying that the answer addresses the question. It integrates with RAG systems.
• DataPrimeCoralogix's query language built for observability. It is an AI-native language to explore, correlate, and transform any data across observability, supporting unified language across telemetry, cross-signal correlation, and transformations. It features a pipe-based expressive syntax, IDE-style editor, schema-aware autocomplete, and AI-assisted query building.
• Streama© architectureAn architecture built for CI/CD that ingests and processes data before storage for low-latency monitoring, fast querying, and zero indexing delays.

Key capabilities

• AI-native observability
• In-stream data processing
• Data storage in customer's cloud (S3 bucket)
• Full data fidelity without indexing or sampling
• Real-time insights across systems, security, and AI workloads
• Conversational AI interface (Olly)
• Ecosystem connectors (Slack, PagerDuty, IDE)
• Command-line interface for automation
• High-cardinality data layer
• Long-term retention
• One data engine across the whole stack
• Cross-signal correlation and joins
• Reusable Datasets
• Open format storage (Parquet)
• Cost optimization tools
• Instant hallucination detection for AI
• Seamless RAG integration for AI evaluation
• Factual accountability for AI outputs
• In-stream analysis & alerting
• Remote, index-free querying
• Unlimited sources for data ingestion
• Enterprise features included (RBAC, SSO, audit trails, compliance controls)
• Unlimited users and hosts
• Scalability (3M+ events/sec, 500K+ applications)
• 24/7 real human support
• APM & Tracing
• Log analytics
• Infrastructure & metrics monitoring
• Real user monitoring (RUM)
• SIEM
• CSPM
• MDR
• Kafka Connect for data ingestion
• Machine learning algorithms for parsing, enrichment, and clustering
• Database monitoring
• Serverless APM
• Service catalog
• Service map
• Continuous profiling
• Network monitoring
• Error tracking
• Session replay
• Infrastructure explorer
• Data enrichment
• Log templating
• Parsing rules
• DataPrime engine
• Cross-stack dashboards
• AI discovery
• App & repo discovery
• AI observability evaluation engine
• Session explorer
• Cost tracking
• AI security and compliance (AI-SPM)
• Edge security with real-time analytics
• In-stream threat detection & correlation
• Granular retention & full-context monitoring
• Security monitoring with SIEM
• Automated detection, investigation, and response for edge threats
• Kubernetes monitoring (multi-cluster intelligence, config-aware troubleshooting, node and pod clarity)
• Time-based analysis for Kubernetes
• Resource behavior over time for Kubernetes
• Flow alerts for Kubernetes events
• Cross-stack correlation for Kubernetes
• Custom dashboards for Kubernetes
• Frictionless Kubernetes integration via OpenTelemetry
• Version-aware CI/CD monitoring
• Native integrations with CI/CD tools (Jenkins, GitHub Actions, ArgoCD, AWS CodeBuild)
• Dynamic routing for CI/CD data
• Integrated version benchmarking
• DORA insights calculation
• Tailored dashboards for CI/CD teams
• Next-gen alerting for fast pipelines
• API reference
• User guides
• Developer portal
• Release notes
• CX CLI (Coralogix CLI)
• OpenTelemetry support

Use cases

• Observability for systems, security, and AI workloads
• Real-time monitoring and troubleshooting
• Cost reduction for observability data
• Data analysis and decision-making using telemetry
• Natural language investigation of production incidents
• Root cause analysis
• Scripting investigations and integrating with CI/CD
• Governing data and driving precise answers
• Building AI strategies on owned data
• Cost optimization for logs, metrics, and traces
• Preventing AI hallucinations and ensuring factual AI outputs
• Real-time AI evaluation
• Compliance and security audits
• Threat investigations
• Historical data analysis
• Monitoring and managing infrastructure at scale
• Detecting anomalies, regressions, or failures
• Incident management
• Debugging
• Edge security and threat detection
• Validating edge defenses
• Correlating edge telemetry with cloud, WAF, CDN, and RUM signals
• Automating detection, investigation, and response for edge threats
• Kubernetes environment monitoring and troubleshooting
• Analyzing resource behavior over time in Kubernetes
• Connecting failing pods to user impact in Kubernetes
• Shipping stable, secure features at pace (CI/CD acceleration)
• Tracking performance across releases with version tags
• Calculating DORA metrics
• Monitoring full CI/CD pipelines
• Long-term stability tracking
• Improving system performance
• Optimizing user experience (UX)
• Forensic investigations
• Building custom solutions via APIs and SDKs

AI approach

Coralogix leverages AI to provide an "AI-native observability platform" with features like Olly, a conversational AI assistant for natural language investigation, and an AI evaluation engine for detecting hallucinations in AI outputs. The platform uses machine learning for in-stream data analysis, parsing, enrichment, and clustering. It also uses AI for security and compliance, and for generating fix suggestions based on code and observability data.

Tech named: Olly, Model Context Protocol (MCP), machine learning algorithms, AI evaluation engine, RAG hallucination evaluator, DataPrime

Industries served

• Software Development
• Fintech
• Gaming Entertainment
• E-commerce
• Logistics
• Healthcare
• Manufacturing
• Retail
• Transportation
• Cybersecurity
• Digital Media
• IoT
• Biometrics
• B2B Communication
• Sustainability (clothing brand)
• Relocation Services
• Research Platforms
• Data Integration
• Fitness
• Insurance
• Public Sector
• Capital Projects Consulting
• Home Renovation

What it says sets it apart

• AI-native platform with a data lake built for observability
• AI-first approach to system investigations (Olly)
• Processes data in-stream and stores it directly in the customer’s cloud
• Delivers full data fidelity without indexing or sampling
• Reduces costs while allowing 100% telemetry data monitoring
• Infinite retention by storing data in customer's S3 bucket in open formats
• Remote, index-free querying of historical data
• One data engine and language (DataPrime) across the whole stack
• Agent-ready from day one with cross-signal correlation and joins
• Cost Optimizer for managing data storage costs
• Real-time AI evaluation engine for hallucination detection
• Unique index-free architecture for scalability
• Unlimited sources, users, and hosts included
• Enterprise features (RBAC, SSO, audit trails, compliance) included in every account
• 24/7 real human support with fast response and resolution times
• Streama© architecture for low-latency monitoring and zero indexing delays
• Version-aware CI/CD monitoring by design
• OpenTelemetry recommended as the telemetry pipeline
• Model Context Protocol (MCP) for connecting AI agents to telemetry
• Proprietary DataPrime query language for observability
• Flexible, tailored pricing model based on units, not tiers