AI Observability in One Platform
Unify every signal across your AI environment so you move from reactive firefighting to strategic, data-driven decision making.
Trusted by Leading Companies
AI Observability Platform
Unified Visibility and True Control Over Your AI Systems
LogicMonitor Envision brings together metrics, events, logs, and traces from your AI systems, on-prem infrastructure, and cloud services into a single view. This AI observability helps you catch issues before they escalate, manage costs effectively, and keep your services reliable.
Get full-stack visibility into your entire AI and IT environment
From LLMs and GPUs to networks and databases—see it all in one unified view, so you can stop context-switching and start solving.
Catch problems and fix them before they impact your customers
When something goes wrong, you’ll know exactly where to look and how to fix it fast. LM Envision spots issues early, and Edwin AI helps you get to the root cause without the usual guesswork or swivel-chairing.
Control your AI budget without lifting a finger
Cut costs and stay on budget by automatically spotting idle resources and wasted compute before they drain your spend.
Grow your AI environment without more tools or headaches
New systems spin up, and LM Envision picks them up automatically, giving you instant visibility without extra licenses or manual setup.
Protect your AI stack from top to bottom
Stay on top of who’s accessing what, from where. If something’s off, you’ll catch it before it becomes an issue.
Generate executive-ready reports in minutes
Quickly turn complex metrics, like AI spend, uptime, and security posture, into clear, executive-ready dashboards that drive alignment and action.
Make your ITOps even smarter
Edwin AI: Agentic AIOps for Incident Management
Edwin AI helps you catch issues early, cut through noise, and resolve incidents fast. With built-in generative AI, it auto-correlates alerts, surfaces root cause, and gives step-by-step guidance to fix problems before customers ever notice.
Built for AI Workloads
Everything you need to monitor, manage, and optimize AI
Comprehensive Monitoring
Unify all your AI-related telemetry to eliminate blind spots.
- GPU & Compute Metrics
Collect utilization, memory usage, temperature, and power-draw data for NVIDIA GPUs—both on-prem and in the cloud—with automatic discovery of new clusters. - LLM & API Telemetry
Ingest token counts, API call latency, error rates, and cost-per-request from OpenAI, AWS Bedrock, Azure OpenAI, and GCP Vertex AI. - Vector Database Visibility
Gather query volume, read/write latency, and index-size metrics from Pinecone and ChromaDB clusters, directly, out of the box.
Dashboards & Visualization
See every AI and infrastructure metric in a single pane of glass.
- Single Pane of Glass
Display LLM, GPU, and vector-DB metrics alongside existing server and network data in one scrollable view. - Prebuilt Templates
Access ready-made AI-focused dashboards that ship with LM Envision. - Custom Dashboards
Build and arrange widgets via drag-and-drop to tailor views for any team or role.
Alerts & Anomaly Detection
Edwin AI learns your environment’s baseline and only surfaces what’s important.
- Anomaly Detection Engine
Automatically flags unusual behavior across LLMs, GPUs, APIs, and pipelines, so you can catch issues early without manual thresholds. - Threshold-Based Alerts
Set custom thresholds for any metric and receive notifications when values exceed or drop below defined limits. - Noise Suppression
Suppress redundant or low-priority alerts automatically, ensuring only high-confidence incidents trigger notifications.
Observability & Correlation
Trace every request to uncover root causes in seconds.
- End-to-End Tracing
Instrument inference pipelines (API call → LLM framework → GPU execution → return) to trace request paths and identify latency bottlenecks. - Service Chain Insights
Capture and correlate metrics from Amazon SageMaker, AWS Q Business, Kubernetes pods, LangChain agents, and other middleware components. - Hybrid-Cloud Topology Mapping
Auto-discover and map relationships between on-prem hosts, cloud VMs, and container clusters—updating maps as new resources spin up.
Cost Optimization & Capacity
Stay ahead of costs with AI spend forecasting and budget recommendations.
- Token Cost Breakdown
Break down AI spend by model, application, or team using built-in cost dashboards. - Idle Resource Detection
Identify idle or under-utilized GPUs and vector-DB shards to highlight opportunities for consolidation. - Forecasting & Budget Alerts
Apply historical metrics to forecast next month’s token spend or GPU usage and configure budget-threshold alerts.
Security & Compliance
Combine service events and security logs to flag unauthorized activity and export audit-ready logs instantly.
- Unified Security Events
Ingest security logs and alerts (firewall, VPN, endpoint) alongside AI-service events—flagging unauthorized API calls, unusual container launches, and data-store access anomalies. - Audit Logging
Store and export logs and metric snapshots for any point in time to support compliance (e.g., HIPAA, SOC 2) and audit reporting.
Open & Agnostic
ITSM Integration
AI Connectors
See What AI Observability Can Do for Your Stack
See how LogicMonitor helps you monitor your AI systems in one place. Your team can move faster with fewer surprises.
Frequently Asked Questions
- What is AI observability?
AI observability is the ability to monitor and understand how AI systems behave in production. It helps teams detect model drift, spot latency, and catch silent failures by combining insights from infrastructure, models, and apps into one view.
- How is AI observability different from traditional monitoring?
Traditional monitoring watches CPU, memory, and uptime. AI observability connects those signals with model behavior, like output changes, performance slowdowns, and unusual agent behaviors.
- When should I implement AI observability?
Ideally before production. It’s much easier to track your AI systems from day one than to fix visibility gaps later.
- Can LogicMonitor detect issues like drift or latency?
Yes. LogicMonitor watches for unusual patterns in system and model behavior, like slow responses, unexpected output spikes, or shifts in usage that often indicate deeper AI issues.
- Do I need agents or custom instrumentation to get started?
No. LogicMonitor uses an agentless model with built-in integrations. You can start monitoring your AI stack quickly, without complex setup.