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AI-Powered + LLM Observability

AI Observability

Two sides of the AI observability coin: use AI to supercharge your monitoring with anomaly detection and automated root cause analysis — and gain full observability into your LLM and AI systems with prompt tracing, token cost tracking, and hallucination detection.

AI-Powered Observability

Leverage artificial intelligence to transform how you detect, diagnose, and resolve incidents across your entire infrastructure.

Anomaly Detection

Machine learning models trained on your system's baseline behavior to automatically detect deviations, spikes, and unusual patterns before they become incidents.

Predictive Alerting

AI-powered forecasting that predicts resource exhaustion, capacity bottlenecks, and degradation trends so you can act before users are impacted.

Automated Root Cause Analysis

Instantly correlate signals across metrics, logs, and traces to pinpoint the root cause of issues, reducing mean time to resolution by up to 90%.

Intelligent Noise Reduction

AI-driven alert grouping and deduplication that cuts through noise, ensuring your team only receives actionable, high-priority notifications.

LLM & AI System Observability

Purpose-built monitoring for your AI/ML pipelines and LLM-powered applications. Get full visibility into every prompt, completion, agent chain, and model interaction.

LLM Call Tracing & Prompt Logs

Distributed tracing for every LLM call — capture prompts, completions, latency, token counts, and model parameters with full context across agent chains and RAG pipelines.

Token Usage & Cost Tracking

Real-time dashboards for token consumption, cost-per-request, and budget burn rate across models (GPT-4, Claude, Gemini, open-source). Set alerts before costs spike.

Hallucination & Drift Detection

Automated quality scoring that flags factual inconsistencies, hallucinated outputs, and output drift over time so your AI applications stay trustworthy.

AI Pipeline Performance

End-to-end latency, throughput, and error rate monitoring across embedding generation, vector search, retrieval-augmented generation, and fine-tuning jobs.

Key Benefits

  • 90% Faster MTTR: AI-driven root cause analysis dramatically reduces the time from alert to resolution
  • 40% LLM Cost Savings: Token usage analytics and optimization recommendations cut AI infrastructure costs
  • 100% Prompt Traceability: Full audit trail of every LLM interaction for debugging, compliance, and quality assurance
  • Hallucination Guardrails: Automated detection of factual drift and quality degradation in AI outputs
  • 75% Less Alert Noise: Intelligent correlation and deduplication eliminates alert fatigue across your teams

Key Features

ML-Based Baselining

Automatic learning of normal system behavior across all metrics and services

Correlation Engine

Cross-signal correlation across metrics, logs, traces, and events in real time

LLM Trace Explorer

Visual trace viewer for LLM chains showing prompt flow, token usage, and latency at each step

Model Comparison

Side-by-side analysis of model performance, cost, and quality across providers and versions

AI Copilot

Natural language interface for querying system health, investigating incidents, and generating reports

Evaluation Pipelines

Automated quality scoring, regression testing, and output evaluation for LLM applications

How It Works

AI-Powered Ops Pipeline

Integrates with your existing monitoring stack to layer intelligent analysis on top of telemetry data.

  • • Integrates with Dynatrace Davis AI and OpenTelemetry
  • • Real-time streaming analysis with sub-second anomaly detection
  • • Continuous model training on your unique system behavior
  • • Feedback loops that improve accuracy over time

LLM Observability Pipeline

Drop-in SDKs and OpenTelemetry-native instrumentation for any LLM framework.

  • • Works with LangChain, LlamaIndex, Semantic Kernel, and custom chains
  • • OpenAI, Anthropic, Google, AWS Bedrock, and open-source model support
  • • OpenTelemetry-native with GenAI semantic conventions
  • • PII redaction and data masking for prompt/completion logs

Ready to Add AI to Your Observability?

Whether you need AI to power your ops or observability for your AI systems, our experts will help you implement the right solution.

Get Started