Compare the Top AI Control Planes for Cloud as of September 2026 - Page 2

  • 1
    Dapple

    Dapple

    Dapple

    Dapple is an Enterprise OS Cloud built for regulated enterprises and AI-native companies that need dedicated AI infrastructure without compromising on isolation, data residency, governance, or performance. It sits between the public cloud and the private data center, combining dedicated, single-tenant GPU infrastructure with orchestration, compliance, connectivity, observability, and operations through one control plane. Topology-aware placement, multi-GPU scheduling, fault-domain isolation, and reserved clusters provide predictable performance without noisy neighbors. Private connectivity extends existing cloud environments directly to dedicated compute, while identity, container orchestration, threat protection, and governance policies continue working across the deployment. Compliance is enforced at the architecture level before workloads execute, supporting in-country data residency, audit requirements, and regulatory frameworks.
  • 2
    Klique

    Klique

    Klique

    Klique is an enterprise AI control plane that centralizes model routing, AI service governance, and compute orchestration across on-premises, cloud, and hybrid environments. The platform routes AI requests to appropriate models based on factors such as cost, latency, policy, and data sensitivity while also directing workloads to suitable infrastructure. It provides centralized controls for budgets, quotas, virtual keys, single sign-on, audit trails, and access policies across users, agents, models, projects, and tools. Klique can manage in-house models, open-source models, third-party APIs, GPU clusters, CPUs, Kubernetes environments, and cloud AI services through a unified layer. Its orchestration capabilities support shared compute pools, fractional GPU usage, priority scheduling, training jobs, data processing, and live model deployments.
  • 3
    Inficy

    Inficy

    Artnames Ltd

    Inficy is a hosted control plane for AI agent execution evidence. It turns captured agent runs into readable, tamper-evident execution records showing tools, services, timing, failures, recoveries, and human interventions. Records can be inspected, exported, and verified offline, with optional independent certification for selected executions through the NexArt infrastructure. Inficy is designed for engineering teams, operators, and risk or audit reviewers running AI agents that take real actions in production systems.