Simulate any negotiation and watch AI agents reach (or fail to reach) a deal. Legal negotiation is broken. An average ICC arbitration costs $1.7M per side and takes 26 months. With OANP, autonomous agents negotiate in real time: – They reveal hidden interests – Generate options – Make offers and counteroffers Every move is tracable with Pareto efficiency, Nash product, BATNA surplus. You can: – Test negotiation strategies before real-world execution – Simulate high-stakes scenarios safely
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Maker
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When I was in Erasmus, I took a course on Harvard Negotiation Principles. After experimenting with multi-agent swarm discussion systems, I thought to myself... this could work for legal stuff.
This week I packaged them it into an open protocol that autonomous agents can execute that I call OANP (Ontology-based Agentic Negotiation Protocol). It utilizes HNP principles under the hood. The assistant agent helps you define your simulation scenario: parties, interests, BATNAs, and issues, you then press SIMULATE.
Watch them disclose intent, argue, propose offers, accept, reject, counter with a mediator in between.
When parties reach agreement, OANP scores the deal on the metrics that matter: Pareto efficiency, Nash bargaining fairness, BATNA surplus per party, and whether value was created or left on the table.
OANP is fully open-source (MIT), and you can plug in any LLM. I’d love your thoughts:
What negotiation would you simulate first?