Your agent topology is a design decision you never made.
We treat multi-agent architecture as a search problem. Evolutionary discovery finds what intuition can't.
Request AccessEvery multi-agent framework ships a default topology. Flat hierarchy. Broadcast communication. Consensus assembly.
That default is silently determining your output quality, your token spend, and your failure modes. Most teams never test it — because until now, there was no way to.
We built an engine that searches the space of organizational architectures.
Not prompt tuning. Not model selection. The structural layer underneath both — how agents coordinate, what information flows where, how decisions get made, who does what. The architecture itself.
We don't just find better structures. We tell you which decisions are load-bearing and which are decorative.
Causal ablation on every architectural choice. Multi-perspective evaluation that eliminates single-model bias. Statistical validation, not vibes.
Backed by a pre-registered experimental protocol
Organizational Architecture Search: Evolutionary Discovery of Optimal Multi-Agent Team Structures
Robinson & Magnus, 2026. 5 falsifiable claims. 15 tasks. 63 runs. Explicit refutation conditions.
Private Beta — San Francisco, 2026
We're looking for teams deploying multi-agent systems in production.
If you're making topology decisions by intuition and wondering what you're leaving on the table — we should talk.
contact@supremum.io