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A SaaS testing and observability platform that validates LLM agent workflows against real production data before deployment.
Added May 25, 2026
8 signals
Companies are hiring engineers who can build, deploy, and maintain LLM agents, RAG pipelines, MCPs, and multi-agent workflows in production environments. The repeated pain signal is that LLM agents break when connected to real data, tools, and operational workflows, making proof-of-concept builds hard to trust and production rollouts risky.
The product provides a validation harness for AI agent workflows, including scenario tests, tool-call tracing, data-grounding checks, regression suites, and failure analysis for real enterprise data tasks. Teams can plug in OpenAI, Anthropic, Vertex AI, MCP servers, RAG pipelines, and multi-agent workflows to identify where agents hallucinate, misuse tools, fail handoffs, or degrade after prompt/model changes.
Multiple companies now need LLM agents embedded directly into products, platforms, IT systems, security workflows, and customer-facing proofs of concept. As agentic workflows move from experiments to production, buyers need reliability tooling instead of relying solely on scarce forward-deployed AI engineers.
No signals available