Symphysis is a config-driven Python package for expert-elicitation surveys using methods like Best-Worst Scaling, Analytic Hierarchy Process (AHP), and hierarchical variants. It runs these against individually configured panels of real AI agents powered by large language models. It is intended as research tooling for decision analysis and multi-agent systems. Licensed under Apache-2.0.
In the AI & ML space, symphysis takes a focused approach. It focuses on conducting structured expert decision-making surveys at scale using configured panels of AI agents. symphysis is an open-source project aimed at researchers. The project is open source (Apache-2.0). It ships for the command line.
It is developed by Sage Khan, and it first shipped in 2026. Key capabilities include Best-Worst Scaling, AHP Surveys, and Multi-Agent Panels.
Summary written by a language model from the project’s public pages.
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