New Relic AI Monitoring, also known as Application Performance Management (APM) for AI, provides oversight across your tech stack to maintain peak performance, ensure compliance, promote quality, and save on costs. Offering easy setup and integration, the platform allows for prompt issue detection and resolution. It enables visualizing the entire AI stack and gaining instant insights for latency testing and cost tracking. Furthermore, the platform ensures responsible AI use by providing features to mitigate bias and hallucinations. With its complete visibility into AI metrics and built-in integrations, New Relic AI Monitoring helps to foster a reliable and responsible AI model environment.
- Insights into Large Language Models (LLMs): Acquire immediate insights for more accurate latency testing, improved response times, and enhanced budget tracking.
- Responsible AI Use: Gain the ability to mitigate bias, toxicity, and hallucination in AI by monitoring response traces.
- Complete Stack Visibility: Obtain an overview of AI metrics, including response time, quality, tokens, APM golden signals, and infrastructure data. It allows for quick problem isolation with a unified view of the AI stack.
- Built-in Integrations: Use integrations for models like OpenAI, vector data like Pinecone, and frameworks like LangChain.
- AI App Performance and Cost Management: Easily manage costs by tracking request tokens used and setting up custom alerts. Quickly compare different models for cost, performance, and quality, all in one view. Monitor and analyze the prompts and responses generated by models for speed, accuracy, and cost impact.
New Relic AI Monitoring, also known as Application Performance Management (APM) for AI, provides oversight across your tech stack to maintain peak performance, ensure compliance, promote quality, and save on costs. Offering easy setup and integration, the platform allows for prompt issue detection and resolution. It enables visualizing the entire AI stack and gaining instant insights for latency testing and cost tracking. Furthermore, the platform ensures responsible AI use by providing features to mitigate bias and hallucinations. With its complete visibility into AI metrics and built-in integrations, New Relic AI Monitoring helps to foster a reliable and responsible AI model environment.
- Insights into Large Language Models (LLMs): Acquire immediate insights for more accurate latency testing, improved response times, and enhanced budget tracking.
- Responsible AI Use: Gain the ability to mitigate bias, toxicity, and hallucination in AI by monitoring response traces.
- Complete Stack Visibility: Obtain an overview of AI metrics, including response time, quality, tokens, APM golden signals, and infrastructure data. It allows for quick problem isolation with a unified view of the AI stack.
- Built-in Integrations: Use integrations for models like OpenAI, vector data like Pinecone, and frameworks like LangChain.
- AI App Performance and Cost Management: Easily manage costs by tracking request tokens used and setting up custom alerts. Quickly compare different models for cost, performance, and quality, all in one view. Monitor and analyze the prompts and responses generated by models for speed, accuracy, and cost impact.