Aliouche Ahouab

1. AI for Infrastructure Cloud optimization (cost, performance, autoscaling) Augmented observability (anomaly detection, intelligent SLOs) SRE + AI (incident prediction, automated remediation) 2. LLMs in controlled environments (sovereignty / on-prem) Private model deployment (Ollama, vLLM) Security, governance, traceability K3s / Proxmox architectures for industrial AI 3. RAG (Retrieval-Augmented Generation) for business use Document ingestion pipelines Vector search (pgvector) Monetizable use cases (audit, compliance, knowledge systems) 4. AI as a high-value service layer AI-enhanced Cloud audits E-invoicing automation and compliance Advisory + integration + SaaS models 5. Data & predictive analytics for investment Real estate (analysis, decision support, arbitrage) Crypto (market cycles, macro correlations, opportunity detection) 6. Underlying technical stack Kubernetes / GitOps for industrialization CI/CD pipelines for ML systems Full observability (metrics, logs, tracing)