Resources for
Governed AI Adoption
White papers, compliance guides, and technical documentation
for regulated enterprises.
EU AI Act Compliance Guide
The EU AI Act is in force, and the Digital Omnibus has reset the timeline for high-risk AI. The operational question is no longer the deadline - it is whether your AI can produce the evidence reviewers will ask for.
Key Dates
practices (in effect)
obligations (in effect)
obligations apply
regulated products
Our guide covers what regulated enterprises need to know: high-risk classification, documentation requirements, and how in-perimeter, governed AI architecture enables compliance by design.
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Get our EU AI Act Compliance Guide for Enterprise AI - what high-risk classification, documentation, and evidence mean for regulated AI.
Realm Insights
Category insight on executable AI governance - new writing from the Realm team.
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New writing on executable AI governance, privacy engineering, and what regulated AI really takes. No spam.
Thought Leadership
Mathematical Sovereignty: A Sovereign AI Strategy
A framework replacing hardware dependency with verifiable cryptography and privacy-by-proof. How REALM enables secure, distributed, regulation-compliant AI.
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REALM: Confidential AI Platform
Strategic overview of how REALM combines Confidential AI, Privacy-Enhancing Technologies, and enterprise governance for secure, explainable AI systems.
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AYITA: Governed Runtime for Regulated AI Work
Governs regulated AI work while it runs - checking consequential actions, keeping named people in the work, and producing an audit-grade trace. Runs entirely within your perimeter.
PAMOLA: Privacy Engineering Studio
Get AI on sensitive data approved. PAMOLA turns sensitive data into provably private, usable AI-ready data and produces a PAMOLA Evidence Pack for review and sign-off.
Ecosystem Data Bridge
Secure data collaboration between enterprises using Zero-Knowledge Proofs and Private Set Intersection. No raw data leaves your perimeter.
Industry Resources
Privacy & AI in Healthcare
Synthetic data, federated learning, and explainable AI for healthcare institutions. HIPAA-compliant AI collaboration without sharing raw patient data.
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Secure Data Processing Framework
Privacy-preserving AI development through synthetic data generation, differential privacy, and federated learning for financial institutions.
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Synthetic Data Generation
AI-generated privacy-preserving datasets using PATE-GAN, DP-Former, and Transformer-based models with Differential Privacy guarantees.
Explainable AI (XAI)
Making AI decisions transparent and interpretable using SHAP, LIME, and Counterfactual Explanations for regulated industries.
REALM Glossary
Key terms for navigating governed AI and privacy engineering. Each definition includes why it matters for your decisions.
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