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A production platform that monitors, debugs, and hardens LLM-powered agent workflows when they break against real-world data.
Added May 23, 2026
8 signals
Teams across data, product, security, and operations are racing to build LLM-powered agents, RAG pipelines, and tool-using workflows, but these systems frequently break when they meet messy real-world data and production environments. Engineers lack purpose-built tooling to detect, diagnose, and prevent these failure modes at scale.
A platform that instruments agent workflows (including multi-agent and A2A orchestration) to trace tool calls, capture data-grounding failures, and surface regressions across LLM providers like OpenAI, Anthropic, and Vertex AI. It provides evaluation harnesses, replay/debugging, and guardrails so engineering teams can ship agents into production with confidence instead of one-off glue code.
Job postings across data infrastructure, SaaS, fintech, aerospace, and observability companies are simultaneously demanding hands-on experience deploying LLM agents in production, signaling that agentic workflows have moved from prototypes to load-bearing systems that need dedicated reliability tooling.
No signals available