Our Mission
Superrank ranks AI models, agents, benchmarks, companies and people on verifiable evidence, with a Superrank Rating, user ratings and popularity.
The rapid proliferation of foundation models and autonomous systems has produced an overwhelming volume of claims, vendor benchmarks, and marketing metrics. Too often, evaluations rely on cherry-picked datasets, opaque scoring methodologies, or paid placements disguised as objective reviews.
Superrank was built as a response: a strictly deterministic, reproducible ranking engine anchored in verifiable third-party benchmarks and Bayesian community ratings. No black boxes, no secret formulas, and no pay-for-placement.
Every feature, schema, and API in Superrank strictly enforces these foundational rules.
Every model, agent, organization, and benchmark is sourced directly from verifiable primary records. Synthetic or placeholder entities are never displayed.
Real platforms start with real empty states. If zero models match a filter, we show an honest message, never populated mock cards.
Every context length, parameter count, and benchmark score stores an immutable source URL and retrieval timestamp for full verification.
All brand logos, icons, and assets maintain transparent licensing attribution, rights-management metadata, and authorized usage.
Defense-in-depth access controls, mandatory multi-factor authentication for administrators, sliding-window rate limiting, and zero hardcoded secrets throughout.
No stubbed or dummy fields; strict schema validation guarantees structural compliance and data integrity across all catalog entries.
All rankings use weighted Bayesian shrinkage with published priors and parameters (m = 25, C = 7.0). Zero pay-to-play manipulation.
Superrank is built on modern, secure cloud infrastructure featuring isolated network subnets, automated web application firewall rate-limiting, hardened user authentication with mandatory MFA for staff, decoupled background pipelines for processing, and strict schema validation across all data stores.
