M P A C
The missing trust layer for AI
Pelidum's Multi-Provider Agent Consensus, or MPAC, compares outputs from multiple AI providers and builds consensus -
so decisions are safer, smarter, and more reliable.
The Problem
- AI's black box is a growing risk.
AI is everywhere, but single-model systems are unpredictable and hard to trust. Relying on just one model means dealing with its weaknesses, too.
- Inconsistent and unpredictable answers erode confidence at the executive and legal level.
- Bias in outputs leads to skewed or unfair results.
- Hallucinations produce factually wrong answers presented as truth.
Blind spots mean no single model can cover every edge case.
the solution - mpac
- The best of all providers.
Different models often disagree — MPAC brings them into consensus for safer, smarter results.
- Request
Send your query to multiple AI models at once, regardless of provider. Choose from 300+ models.
Consensus
MPAC aggregates and compares their outputs using advanced logic.
Validate
MPAC returns a single, validated answer with confidence scores and an audit trail.
Deploy
Available as a SaaS API or as a secure on-premises solution for sensitive data.
WhO Needs MPAC?
- From platforms to public trust: reliable AI, real-world results.
Accuracy
Lower error rates than single-model systems.
Fairness
Reduced bias through multi-perspective validation.
Transparency
Clear logic when providers disagree.
Sovereignty
Reducing dependence on single providers.
Scalability
Works across workflows, from moderation to analytics.
Built to evolve with the AI landscape.
See MPAC in Action
Experience how consensus across providers makes AI safer and more reliable.
