# VDF AI VDF AI est une plateforme d’orchestration d’agents IA pour les entreprises, qui coordonne agents, modèles, outils, recherche et workflows sous une gouvernance centralisée. Elle s’utilise en service cloud géré ou se déploie dans un cloud privé, un centre de données, un environnement souverain, un compte AWS ou une infrastructure isolée. - Findings24: - Site web: - Tarifs: Freemium - Catégories: Developer Tools ## Qu'est-ce que VDF AI ? VDF AI is an enterprise AI orchestration platform for turning AI agents and models into governed workflows. It coordinates multi-agent execution, retrieval from enterprise knowledge sources, model selection, tool calls, approvals, and result validation while recording the execution path for review. The platform is available as a managed cloud service or as a self-deployed installation in a data centre, private cloud, sovereign environment, AWS account, or air-gapped setting. Its product suite includes VDF AI Networks for multi-agent orchestration, VDF AI Agents for deployable agent workflows, VDF AI Chat for private-RAG conversations, and VDF AI Data for data preparation and model validation. ## Que peut faire VDF AI ? ### Governed multi-agent Networks Decompose a request into typed sub-tasks, map dependencies, select agents, tools, and models at runtime, and validate the result before returning it. Execution paths are recorded. ### Enterprise retrieval and knowledge grounding Use private RAG and knowledge-graph capabilities to ground responses in connected enterprise information rather than relying only on pasted context. ### Runtime model routing Select models against task complexity, cost, latency, and capability. Routing decisions are logged for operational review. ### Workflow governance and audit trails Apply centralized controls for access, permissions, policies, retrieval, tool calls, and execution logging so decisions can be reconstructed later. ### Private deployment options Run the platform in VDF AI’s managed cloud or deploy it on private infrastructure, including on-premises, private-cloud, sovereign, and air-gapped environments. ### Usage and operational reporting Monitor cost and energy metrics, usage, execution activity, and governance data. Capacity licensing includes dashboards, monthly consumption statements, and usage alerts. ## Cas d'utilisation ### Private knowledge assistants Build chat or agent experiences that retrieve information from private enterprise sources while keeping the data and deployment under the organization’s control. ### Complex cross-system workflows Coordinate multiple agents, models, tools, APIs, databases, business systems, decisions, and approval steps as one repeatable workflow. ### Model-cost optimization Route different tasks to suitable models based on complexity, latency, capability, and cost, then review the routing and usage records. ### Regulated or sovereign AI operations Operate agents and retrieval inside a company data centre, private or sovereign environment, or disconnected infrastructure where external API dependencies are not acceptable. ### Production AI operations Move a validated use case from a pilot into a controlled production workflow with defined inputs, owners, access controls, monitoring, and auditable execution records. ## Questions fréquentes ### Where can VDF AI run? VDF AI can run as a managed cloud service or be deployed on an organization’s infrastructure, including a data centre, private cloud, sovereign environment, AWS account, or air-gapped environment. The on-premises platform uses container deployment. ### How does a request move through the platform? VDF AI parses intent, breaks the request into typed sub-tasks, maps dependencies, selects agents, tools, and models, coordinates work that may run in parallel, validates the result, and records the execution path and outcome. ### Does VDF AI support private enterprise data? Yes. The platform provides enterprise RAG and knowledge-graph grounding, and its deployment options are intended for organizations that need to keep data, models, agents, and infrastructure within their own perimeter. ### How is on-premises usage licensed? On-premises capacity licensing uses an annual organization-wide pool with separate token and platform-transaction meters. Capacity is shared across included environments, while human users are unlimited. VDF AI provides a usage dashboard, monthly consumption statements, and alerts. ### Can teams start without buying an on-premises capacity bundle? The managed cloud version has a free Starter plan with no credit card required. VDF AI also describes a controlled 90-day pilot for on-premises evaluation, with a defined allowance, throughput ceiling, and one non-production environment; the pilot fee is credited toward an annual Capacity Bundle ordered shortly afterward. ## Informations rapides - **Category**: Enterprise AI platform - **Primary functions**: AI agent orchestration, private RAG, model routing, workflow governance - **Deployment**: Managed cloud, private cloud, on-premises, sovereign, or air-gapped - **Products**: VDF AI Networks, VDF AI Agents, VDF AI Chat, and VDF AI Data - **Cloud entry point**: Free Starter plan; no credit card required - **Pricing model**: Cloud plans and annual on-premises capacity licensing