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The industry's first all-in-one observability platform for the complete AI stack.

New Relic AI Monitoring (AIM) represents a pivotal shift in 2026 observability architecture, moving beyond traditional APM into deep-tier LLM application performance management. It provides a unified view of the entire AI stack—from infrastructure and vector databases to the LLM orchestration layer. Technically, it integrates via OpenTelemetry and proprietary agents to capture traces, prompts, and responses, enabling real-time detection of hallucinations, PII leakage, and toxic content. By correlating LLM performance with underlying infrastructure metrics (GPU utilization, memory saturation), New Relic AIM allows site reliability engineers (SREs) to diagnose bottlenecks that occur at the intersection of traditional compute and neural inference. As of 2026, its market position is solidified by 'New Relic Grok,' a generative AI assistant that allows engineers to query telemetry data using natural language, effectively lowering the barrier for complex NRQL (New Relic Query Language) operations and accelerating root cause analysis (RCA) across distributed microservices.
New Relic AI Monitoring (AIM) represents a pivotal shift in 2026 observability architecture, moving beyond traditional APM into deep-tier LLM application performance management.
Explore all tools that specialize in token usage tracking. This domain focus ensures New Relic AI Monitoring (AIM) delivers optimized results for this specific requirement.
End-to-end visibility from the user request down to the LLM API call and back, including middleware and database lookups.
Generative AI assistant that writes NRQL queries and explains system anomalies using LLMs.
Automated scoring of LLM responses for toxicity, sentiment, and factual consistency.
Real-time tracking of token consumption mapped to dollar amounts based on specific LLM provider pricing.
Monitoring query performance for vector databases like Pinecone, Weaviate, and Milvus.
Regex and ML-based detection and redaction of sensitive information in prompts before ingest.
Side-by-side performance comparison of different LLMs (e.g., GPT-4 vs Claude 3).
Create a New Relic account and obtain your license key.
Install the New Relic APM agent (v10.15+ for AI support) in your application environment.
Initialize the New Relic SDK within your LLM orchestration code (LangChain, LlamaIndex, or native).
Configure environment variables for LLM metadata tracking (Model Name, Provider).
Define 'custom attributes' in your application to capture prompt and response tokens.
Navigate to the 'AI Monitoring' tab in the New Relic UI to see auto-discovered LLM entities.
Set up 'Lookback' windows to compare model performance version-over-version.
Configure 'Drop Rules' for PII data to ensure compliance with GDPR/SOC2.
Enable 'New Relic Grok' to start using natural language for dashboard generation.
Establish Baseline Alerts for LLM response latency and token cost spikes.
All Set
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"Users praise the deep integration between AI and infrastructure, though some find the NRQL learning curve and consumption-based pricing complex to manage."
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