Data
Models
Agents
Test
Optimized
Validated
Trusted
The all-in-one platform For AI and agentic testing, optimization and validation.
Test, tune, and validate the intelligence driving your business.
Designed for banks, fintechs, and insurance carriers that need precision, speed, and proof.
Accelerate risk reviews. Cut onboarding by weeks. Stay exam-ready.
Test high-risk AI models and agents
Comprehensive testing for bias and fairness.
Optimize model and agentic performance
Maximize accuracy while ensuring compliance.
Govern traditional, ML, and agentic systems
Comprehensive testing for bias and fairness.
Test and Validate
The Challenge
Financial institutions are deploying AI faster than they can validate it.
Traditional approaches can’t keep pace.
Proven Impact
Real results from enterprise deployments.
12x FTEs
Average financial institution staffing shortage.
Model validation teams lack the resources to keep pace with AI development and deployment needs.
$500K+
Annual external validation costs.
Manual processes and consulting fees drain budgets while teams wait for results.
61%
High-risk models infrequently validated (OCC).
Most high-risk models lack regular validation, creating significant compliance gaps.
The FairPlay Advantage
Complete AI validation services that accelerate compliance and reduce risk.
Days, not months
Model validation teams lack the resources to keep pace with AI development and deployment needs.
30–60% cost reduction
Cut consulting and manual testing spend
3x validation capacity
Without adding headcount
Exam-ready documentation
Regulatory-aligned evidence from day one
Trusted by Leading Financial Institutions
Solutions that Accelerate AI Adoption
One platform. Built for performance, speed, and safety. Govern all your intelligent systems—from scorecards to agents—with confidence and clarity.
Build
Test
Optimize
Validate
Govern
Model Validation
Automated SR 11-7 compliant validation with exam-ready documentation.
SR 11-7 Aligned
Automated Bias Testing
Test before production, monitor after deployment, surface less discriminatory alternatives, and automate fair lending reporting.
Fair Lending
Agentic Evaluations
Domain-specific evaluations for AI agents in financial services. Test how well agents actually do their jobs.
NIST AI RMF
Model Optimization
Improve approval rates and financial inclusion without increasing risk. Unlock revenue your current models leave behind.
Revenue Impact
Tools that increase performance, shorten risk reviews, lower consulting spend, and keep you exam-ready.
Platform Overview
See exactly how we transform your AI governance from months to days.
Automated Bias Testing
See exactly how we transform your AI governance from months to days.
- Test any model, any time — underwriting, pricing, third-party scores and more
- Bias detection across protected classes and geographies
- Regulator-ready reports aligned to ECOA/Reg B
- Peer benchmarking to see where you lead or lag on inclusion
- Fairness Monitoring: Continuous automated surveillance to detect emerging disparities
Model Validation
Full independent validation in days; optional independent attestation.
- Full independent validation in days
- Automates all mandatory statistical testing, including production-level stress and robustness checks
- Auto-generates every section of SR 11-7 documentation by ingesting existing model files and industry templates
- Validate internal and vendor-built models
Agentic AI Validation
The first independent evaluation solution for AI agents.
- Run General-Purpose and domain-specific evaluations to ensure agent reliability.
- Prove your agents are effective, safe, and compliant.
- Aligned with SR 11-7, NIST, and OWASP standards.
- Built for sellers, buyers, and developers of AI agents.
Model Citizens
Featured Podcast
AI Compliance for Banks and Fintech Leaders
Download Resources
Join leading financial institutions in building trusted AI systems.
Model Validation Field Guide
The AI Exam Readiness Handbook
Fair Lending Math
Your Ready to Transform Your AI Validation?
Join leading financial institutions in building trusted AI systems.