Most AI agents fail in production, and teams end up stitching together evals, observability, and guardrails that never close the loop. Future AGI collapses all of it into one platform: simulate edge cases before launch, evaluate what happens in production, protect users in real time, and feed every trace back into the next version.
What you get
🧪 Simulate: thousands of multi-turn text + voice conversations against realistic personas and adversarial inputs
📊 Evaluate: 50+ metrics under one evaluate() call (groundedness, tool-use, PII, custom rubrics)
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
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