Why deploy observability for AI on your cloud, anyways?

Groundcover has introduced AI Observability, utilizing the Berkeley Packet Filter-powered sensor in a bring-your-own-cloud (BYOC) model, to address the limitations of traditional observability systems for agentic applications, which often lead to privacy and economic issues. This platform allows users to have comprehensive visibility into their large language models (LLM) and agentic workloads without extra costs, providing insights into prompts, responses, tokens, and latency, and unifying LLM usage costs. The integration of Agent Mode enables development and SRE teams to enhance remediation efforts and streamline investigations through intelligent prompts and automated workflows, ensuring full context is available without the need for data sampling. Groundcover's approach permits data retention directly within the customer's cloud, eliminating the privacy concerns and unexpected costs associated with traditional SaaS observability solutions, and allowing organizations to deploy agentic applications confidently in production environments.

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