AI Governance & Assurance
We validate, govern and prove your AI. Independent model validation, bias, fairness and explainability testing, and audit-ready evidence mapped to the EU AI Act, RBI FREE-AI and model-risk expectations, so you can put your name behind every automated decision.
The AI making your decisions needs someone to answer for it
Unproven by default
- No inventory of the models in use
- Decisions you cannot explain
- Compliance discovered at audit
Validated and provable
- Every model inventoried and risk-tiered
- Decisions explained and evidenced
- Compliance built in and continuous
Prove it before the regulator asks
We inventory and risk-tier every model, validate it independently, and produce the evidence, then keep it under continuous assurance.
Inventory and risk-tier
Find every model, agent and automated decision, and classify each against the EU AI Act, RBI FREE-AI and model-risk expectations.
Validate independently
Test performance, bias and fairness, explainability, robustness and drift, independent of the team that built it.
Evidence and document
Produce the audit-ready pack: model cards, validation reports and control mapping to each regime.
Monitor and re-attest
Continuous monitoring, drift and incident logging, and periodic re-validation.
What we deliver
Independent model validation
Performance, bias, explainability and robustness testing, independent of the builder.
Model inventory & risk-tiering
A live register of every AI system, classified by risk.
Bias, fairness & explainability
Fairness testing and interpretable explanations for consequential decisions.
Audit-ready evidence
Model cards, validation reports and regulator-mapped documentation.
Regulatory readiness
EU AI Act, RBI FREE-AI, India's DPDP Act and model-risk (SR 11-7 / SR 26-2) alignment.
Continuous assurance
Monitoring, drift detection, incident reporting and periodic re-validation.
- EU AI Act high-risk readiness for credit, insurance and lending models
- RBI FREE-AI assurance for Indian banks and NBFCs
- Independent validation of credit, AML and fraud models
- Enterprise-wide model inventory and risk-tiering
- Bias, fairness and explainability testing for automated decisions
- Board-level AI governance policy and audit trails
Fits into your existing stack
Neulaxy solutions integrate with the systems, tools, data and processes you already use, through clean and well-documented APIs. We fit into your stack rather than asking you to rip out and replace what works.
Frequently asked questions
What is the difference between AI security and AI governance?+
Security defends your AI from attack; governance proves it works, is fair and complies. Different questions, different owners. We do both, as separate disciplines.
What is independent model validation?+
Testing of a model by someone other than its builder, covering performance, bias, explainability and robustness. It is the core expectation in model-risk and AI regulation.
Which regulations do you cover?+
The EU AI Act, RBI's FREE-AI framework, India's DPDP Act, and model-risk expectations (SR 11-7 / SR 26-2), with alignment to NIST AI RMF and ISO/IEC 42001.
We are an Indian bank or NBFC. Where do we start?+
With RBI FREE-AI: a model inventory, a board-approved AI policy, and independent validation of your highest-risk models such as credit, AML and fraud.
Can you validate AI we did not build?+
Yes, independence is the point. We assess, validate and evidence models and agents built by your own team or by third parties.
Do you govern generative and agentic AI?+
Yes. Current model-risk rules largely leave agentic AI out of scope, so we apply extra oversight such as tight permissions, human-in-the-loop and monitoring, designed for autonomous systems.
Need to secure your AI, not just prove it?
AI SecurityReady to prove your AI?
Book a 30-minute consultation and we will map the highest-leverage first use case.