AL360° Platform
AffectLog’s AL360° platform transforms how regulated industries deploy AI by combining federated execution, automated compliance reasoning, and cryptographic governance. Raw data never leaves its secure perimeter — while real-time risk, bias, and conformity metrics are continuously updated through privacy-preserving, distributed orchestration.
300+
Active Federated Nodes
20+
Compliance Modules
3
Advanced Privacy Layers
$0
Data Breaches
Future of AI Compliance Orchestration
100+
Dynamic Policy Updates
At the intersection of federated AI, automated legal mapping, and high-assurance privacy architectures, AL360° powers secure, scalable, and regulation-aligned AI operations for mission-critical use cases.
Federated Orchestration Engine
Run distributed AI workloads on-premise or in sovereign clouds, exchanging only encrypted model and risk updates — not raw data.
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Automated Compliance Layer
Continuously map model behaviours against evolving frameworks (EU AI Act, GDPR, HIPAA, ISO 42001) with zero manual overhead.
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Self-Sovereign Governance
Anchor every compliance decision, audit log, and policy update in an immutable, immutable and secured ledger.
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Dynamic Policy Enforcement
Trigger automatic interventions (bias mitigation, retraining, access restriction) the moment non-compliance is detected.
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Expanding the Frontiers of Federated AI Compliance
AL360° delivers enterprise-grade, configurable pipelines for risk scoring, fairness evaluation, explainability, and governance automation. By fusing federated computation with real-time compliance monitoring, AL360° connects global AI ecosystems without breaching trust or legal boundaries.
Beyond Traditional Governance Tools
Each processing capsule runs in transient, encrypted enclaves — ensuring no residual data or compliance artefacts persist after analysis.
Synergy of AI + Legal Reasoning
AL360° synchronises federated ML pipelines with regulatory ontologies, enabling dynamic, context-aware compliance scoring across sectors.
Unlock the Potential of Federated Compliance Intelligence
From validating hospital diagnostic models to securing public-sector AI deployments, AL360° scales across any AI lifecycle — enabling lawful, fair, and explainable systems by design.
“AffectLog se distingue par son approche novatrice combinant l’évaluation des risques de l’IA avec des espaces de données éphémères, permettant d’assurer des audits IA tout en respectant strictement la confidentialité des données. Son architecture fédérée garantit que les données sensibles ne quittent jamais leur environnement d’origine, tout en permettant des évaluations rigoureuses et automatisées de la conformité algorithmique. “
Grégoire Borst
Directeur du Laboratoire de Psychologie du Développement et de l’Education de l’enfant (UMR CNRS 8240)
“What sets AffectLog apart is its capacity to operationalize complex regulatory principles—such as fairness, transparency, and explainability—into a scalable and usable platform. Roy’s solution is both technically advanced and socially aligned, providing practical tools for organizations like ours to manage algorithmic risks while upholding ethical standards. AffectLog is not only innovative; it is urgently relevant. As governments and organizations face increasing obligations under emerging legal frameworks, the need for robust, audit-ready AI infrastructure is clear.”
Caroline Jenner
Chief Operating Officer, JA Worldwide
“AffectLog est une initiative intrisequement innovante, qui répond aux défis critiques de l’éthique et de la transparence de l’IA, en s’attaquant à la gestion responsable des données dans les systèmes d’apprentissage automatique. Son approche, basée sur des espaces de données éphémères et l’évaluation des risques IA en architecture fédérée, représente une avancée significative pour la protection de la confidentialité et la conformité aux réglementations européennes (EU AI Act, RGPD).”
Franck Zenasni
Directeur adjoint de l’UMR LaPEA, Expert référent SHS au MCSER
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Harness federated AI and compliance automation to run high-impact, regulation-aligned AI at scale.
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