Ployos replaces experimental RLHF with mathematically guaranteed Ground Truth — via the proprietary 3+1 Consensus Engine.
Pilot launch window for qualified enterprise data projects
Quad-verification protocol across experts and Shadow AI
Native speakers, engineers, clinicians, quants, and safety researchers review outputs against the same ground-truth protocol.
Independent evaluations, blind arbitration, and Shadow AI checks keep noisy reward signals out of production datasets.
Prepaid project budgets, audit trails, and API-ready outputs let enterprise teams move from pilot to production without finance drag.
Connect your data, configure your consensus parameters, and let Ployos begin improving signal quality immediately.
Pilot launch window for qualified enterprise projects
Average consensus rate across all active tracks
Upload your dataset, set evaluation criteria, and configure 3+1 consensus parameters.
Ployos assigns domain-certified specialists per task. Blind parallel evaluation begins immediately.
Consensus-locked data ships via API with a full audit trail. Rejected signals are not billed.
A single, continuous pipeline from expert human consensus to mathematically guaranteed benchmark performance.
No shared context. Strictly against the mathematical constraints of your reward model.
Identical prompt. Blind to peer judgments. Effectively eliminates anchoring bias.
Blind third-party arbitration. Triggers automatically on H1/H2 disagreement.
Autonomous semantic validation. All four signals must match before data ships.
Decreased unverifiable claims in legal/medical tracks by enforcing mathematical consensus.
Scaled native-speaker validation across MENA markets, achieving total consensus.
Traditional labelling relies on unverified crowd-workers with no consensus mechanism. Ployos uses a 3+1 quad-verification protocol where three independent human experts and a Shadow AI agent must all agree before any signal is accepted. This eliminates noise at the source.
