Déploiement

AI Orchestration

Définition

The coordination of multiple AI models, tools, APIs, and data sources within complex automated pipelines or agentic workflows. Orchestration frameworks like LangChain, LlamaIndex, and Temporal manage state, retries, and branching logic across multi-step AI processes.

Termes Connexes

Agentic AI

AI systems that autonomously plan, reason, and execute multi-step tasks over extended time horizons without continuous human direction. Agentic AI is moving from demo to production in 2025–26, raising new questions around oversight, auditability, and the EU AI Act's human oversight requirements.

MLOps

The practice of combining Machine Learning, DevOps, and data engineering to streamline the deployment, monitoring, and maintenance of ML models in production. MLOps ensures reliable, scalable, and reproducible ML systems across their entire lifecycle.

LLMOps

An extension of MLOps focused on the operational challenges specific to large language models: prompt management, context handling, latency optimisation, cost control, hallucination monitoring, and compliance logging. LLMOps tooling is rapidly maturing in 2025–26.

Services Connexes

Pilot To Production

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