Mediator.ai – Using Nash bargaining and LLMs to systematize fairness
Eight years ago, my then-fiancée and I decided to get a prenup, so we hired a local mediator. The meetings were useful, but I felt there was no systematic process to produce a final agreement. So I started to think about this problem, and after a bit of research, I discovered the Nash bargaining solution. Yet if John Nash had solved negotiation in the 1950s, why did it seem like nobody was using it today? The issue was that Nash's solution required that each party to the negotiation provide a "utility function", which could take a set of deal terms and produce a utility number. But even…
In plain words
Mediator.ai uses Nash bargaining theory combined with large language models to systematize dispute resolution and contract negotiation. Rather than requiring parties to manually define utility functions, the system uses LLMs to compare deal terms and estimate preferences, then applies Nash's mathematical solution to find fair agreements. The tool is designed for couples negotiating prenups, divorces, business partners in disputes, and others seeking systematic mediation guidance. It stands out by applying decades-old game theory to modern negotiation problems in an automated, systematic way.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Eight years ago, my then-fiancée and I decided to get a prenup, so we hired a local mediator. The meetings were useful, but I felt there was no systematic process to produce a final agreement. So I started to think about this problem, and after a bit of research, I discovered the Nash bargaining solution. Yet if John Nash had solved negotiation in the 1950s, why did it seem like nobody was using it today? The issue was that Nash's solution required that each party to the negotiation provide a "utility function", which could take a set of deal terms and produce a utility number. But even experts have trouble producing such functions for non-trivial negotiations. A few years passed and LLMs appeared, and about a year ago I realized that while LLMs aren’t good at directly producing utility estimates, they are good at doing comparisons, and this can be used to estimate utilities of draft agreements. This is the basis for Mediator.ai, which I soft-launched over the weekend. Be interviewed by an LLM to capture your preferences and then invite the other party or parties to do the same. These preferences are then used as the fitness function for a genetic algorithm to find an agreement all parties are likely to agree to. An article with more technical detail: https://mediator.ai/blog/ai-negotiation-nash-bargaining/
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