New Relic’s market-leading AI monitoring provides model comparison capabilities to help enterprises optimize quality, performance, and cost for DeepSeek
New Relic, a leader in Intelligent Observability, has unveiled the industry’s first comprehensive monitoring solution for DeepSeek, aimed at simplifying the development, deployment, and monitoring of generative AI (GenAI) applications. This new offering extends support for DeepSeek and DeepSeek on Microsoft Azure AI Foundry, providing customers with seamless AI stack visibility, simplified integration, and enhanced data security. By combining New Relic’s AI monitoring with DeepSeek’s cost-efficient, high-performance open-source models, businesses can accelerate AI adoption and innovation while maximizing return on investment (ROI).
Observability: A Critical Factor in AI Model Selection and Deployment
As Gartner predicts that more than 80% of enterprises will leverage GenAI or deploy AI-powered applications by 2026, organizations must navigate the complexities of selecting the most effective AI models. With enterprises often working across multiple AI models simultaneously, making informed choices is essential to maintaining a competitive edge.
New Relic equips businesses with real-time, end-to-end observability across their AI application stack—including services, infrastructure, and AI layers—ensuring operational efficiency, reliability, and cost-effectiveness.
“There are a steady release of new models like DeepSeek, Alibaba’s Qwen2.5-Max, and more, and organizations cannot afford to make the wrong AI implementation decisions in today’s hyper-competitive market,” said New Relic CEO Ashan Willy. “Observability solves this challenge by providing visibility across the AI stack. We are pioneering AI observability and extending our platform to include AI apps built with DeepSeek so enterprises can make the right decisions on which AI models to deploy and where to use them. Combining DeepSeek’s cost-effective AI models with our expertise in observability and APM gives enterprises a competitive edge in the AI race.”
Also Read: Apexon Named Leader in ISG Generative AI & Analytics Reports
Maximizing ROI with New Relic’s AI Monitoring for DeepSeek
AI-driven applications introduce complexities, security risks, and significant costs. New Relic’s AI monitoring solution delivers deep insights into key performance metrics such as throughput, latency, and token usage while maintaining robust data privacy protections. It also enables tracing of request flows across services and AI models, offering businesses a clear understanding of their AI applications’ inner workings.
By integrating New Relic’s monitoring capabilities with DeepSeek’s high-performance models, businesses can streamline AI adoption and overcome the challenges of model selection and optimization in an increasingly saturated market. This powerful combination empowers companies of all sizes to leverage AI confidently, drive innovation, and sustain a competitive advantage.
Key Benefits of New Relic’s AI Monitoring for DeepSeek:
- Enhanced Reliability & Performance: Gain comprehensive visibility into DeepSeek-powered AI applications to quickly detect and resolve performance issues.
- Optimized AI Costs: Reduce AI development expenses with cost-effective DeepSeek models and real-time token usage insights from New Relic.
- Informed Model Selection: Leverage New Relic’s unique model comparison features to evaluate the impact of switching between AI models on app performance and token usage.
- Accelerated AI Innovation: Harness the power of DeepSeek’s open models and New Relic’s AI monitoring to drive faster AI deployments and innovation.
Expanding New Relic’s AI Ecosystem with DeepSeek Integration
The DeepSeek integration is the latest addition to New Relic’s growing AI monitoring ecosystem, which recently expanded to include Nvidia NIM and Amazon Bedrock. With over 60 AI integrations—including OpenAI, Claude, Langchain, and Pinecone—New Relic continues to offer the most comprehensive observability solutions, helping enterprises optimize and scale their AI initiatives effectively.