Show HN: Eevo – Consequential Decision Model

Category: ai-ml

Tags: decision-making, ai-agents, expected-value, habermas-machine, calibration

Score: 6.0/10 (Innovation: 7, Technical: 6, Documentation: 6, Utility: 5)

Eevo is a 'consequential decision model' from Upright that helps AI agents make judgement calls by estimating expected value and calibrated probabilities for each option based on stakeholder interests. It comes from a dataset and prompted model for the Habermas Machine (AI for democratic deliberation), but the landing page pitches a commercial API/MCP product for agent decision-making.

Target audience: AI agent developers, backend engineers, devops, and product teams building autonomous systems

Repository: https://www.uprightproject.com/eevo/ · Python · Apache-2.0 · 119 stars

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