One AI gives you one opinion — confidently, even when it's wrong. DevOp convenes a team of models that research, debate, red-team, and reach consensus, so what you get back has been challenged, not just generated. The difference between asking a stranger and convening a room of experts.
Models gather evidence in parallel.
They argue it, surfacing disagreement.
Claims get checked against evidence.
A model attacks the answer to break it.
What survives is synthesized into one view.
A final pass grades and explains it.
Frontier and open models — OpenAI, Anthropic, DeepSeek, Moonshot, Google, NVIDIA, and local Ollama — callable as one team. Pick who's in the room; DevOp runs them, reconciles them, and hands you the synthesis.
A single model's confidence is uncorrelated with its correctness. Diversity is the fix: models that fail differently catch each other's mistakes. DevOp turns that into a repeatable process — research, dissent, refutation, consensus — instead of a dice roll on one response.
The last answer you'll have to second-guess.