The Agent Network Manifesto
Six principles that define how we build, deploy, and govern autonomous sports intelligence.
Why We Built This
The sports intelligence industry is broken. Single-model predictions sold as certainty. Black-box algorithms with no accountability. Historical accuracy claimed without audit trails. Subscription services that profit from your confusion.
We started with a question: what would sports intelligence look like if it were built from first principles?
The answer was a network — not a model. A system of autonomous agents that observe, analyze, validate, and report through consensus. Where every output is verified by multiple independent agents. Where uncertainty is flagged, not hidden. Where post-match audits feed directly back into calibration.
This is the Agent Network Protocol. And these are its founding principles.
Six Principles. Zero Compromises.
Verification Over Prediction
We do not predict. We verify. Every output is the result of multi-agent consensus, not single-model speculation. The network exists to challenge its own assumptions.
Transparency as Protocol
Every signal, every confidence score, every agent decision path is traceable. Black boxes are not intelligence — they are liability. We build glass boxes.
Agents, Not Models
A model generates text. An agent takes action. Our network deploys autonomous agents that observe, reason, validate, and report — each with defined responsibilities and accountability.
Institutional-Grade by Default
What we build for users is the same infrastructure we build for institutions. There is no consumer-grade shortcut. Rigor is not a premium feature — it is the baseline.
The Network is the Product
No single agent is the product. The coordination protocol — the way agents challenge, verify, and refine each other — is what creates intelligence. The network effect is literal.
Post-Match Accountability
Every output is audited against reality. We do not hide from outcomes. Post-match verification loops feed directly back into agent calibration. The system learns from truth.