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Learn how to build reliable, secure, and performant AI agents using the Fabrix.AI AgentOps platform in this 29-minute conference presentation. Discover how Fabrix.AI evolved from Cloudfabrics.com to address the growing demand for agentic functionality, moving beyond traditional AIOps that relies on manual remediation to autonomous or semi-autonomous workflows powered by Large Language Models. Explore the real-world challenges that drive this evolution, including the non-deterministic nature of LLMs, context and data management at scale, and the complexities of connecting to diverse data sources that can lead to hallucination and the "agentic value gap" between experimental demos and enterprise value. Understand Fabrix.AI's proprietary middleware solution that serves as a critical intermediary between AI agents/LLMs and various data sources, featuring the Context Engine that ensures "purity of context" by providing curated, summarized data to prevent context corruption and reduce hallucination while maintaining state across interactions. Examine the Universal Tooling component that dynamically connects to over 1,700 disparate data sources, including MCP-enabled endpoints, API-based systems, and raw or legacy data, by creating necessary wrappers and normalizing data schemas for LLM understanding. Learn about the platform's purpose-built design for real-time data environments, its "co-pilot" for conversational queries, and "Agent Studio" for building custom agents, along with its library of 50 out-of-the-box agents across AIOps, Observability, SecOps, and BizOps. Discover how the AgentOps model operationalizes agents through trust via prompt templates and dynamic instructions, governance through FinOps models, security via a "least agency" principle, and comprehensive observability at the agentic layer with audit trails and real-time flow maps, positioning Fabrix.AI as an enterprise-grade platform that enhances existing observability and ITOM tools.
