Argmin AI - Test AI agent workflows without ML expertise
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For teams and founders shipping agentic AI workflows and features. Generic metrics don't speak your product's language, so a new prompt, model, or RAG change can pass them and still ship real issues. A quick manual check catches even less. You don't need annotated data, an ML team, or a month to be safe from regression. Drop in your agent's task, business rules, docs, and examples, and Argmin AI builds an evaluation you run before every change.
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the way it builds evals from your own task description and docs instead of forcing you to hand-label data is a really thoughtful move for shipping agent features fast.
@adnancwzc Thanks Adnan. That was the whole bet: hand-labeling is where most teams stall out and quietly give up on evals, so if we can bootstrap from what you already wrote (the task description, the docs), you get to a real eval before you ship instead of three sprints later. What are you building agents for?
LLMOps.Space
You don't know what you don't know. If you're building agentic AI workflows and don't have a robust eval system, you're flying blind. This is a really cool solution.
@david_arakelian Flying blind is the right phrase, David. The scary part isn't the failures you catch in the demo, it's the confident-wrong outputs that look fine and ship anyway. That's the whole reason to have an eval you trust before you're in prod, not after. Appreciate you saying so, especially from someone living in LLMOps day to day.