We provision GPU clusters from bare rack to production in under an hour, activate models in under a second, and keep every GPU dollar working — not waiting on storage, restarts, or the cloud.
AI adoption is accelerating, but on-prem GPU clusters are crippled by operational friction that burns compute budgets and stalls production inference.
Every checkpoint reload requires weight copies, engine restarts, and reloads. On a cluster of NVIDIA and AMD GPUs, that idle time costs thousands of dollars per occurrence.
RAG pipelines, agentic systems, and multi-modal workflows stall on storage reads. Legacy POSIX filesystems choke on the small-object metadata patterns that AI inference generates.
Agentic and multi-modal systems lose state across restarts. In mission-critical deployments — finance, healthcare, defense — that means downtime risk and data loss.
Enterprises demand on-premises control for data residency, latency, and cost. But the tooling to run bare-metal AI at cloud-grade manageability doesn't exist. Until now.
Provision, store, activate. One platform from PXE boot to production inference — no Kubernetes, no virtualization, no cloud dependency.
Deploy and configure hundreds of GPU nodes in ~1 hour via PXE boot and immutable OS images. Stateless design — any node can be replaced without cluster reconfiguration.
End-to-end deployment, monitoring, and recovery of high-performance storage clusters built on DAOS. Offline-resilient architecture ensures storage continuity even during network partitions.
Atomic registry pointer swap in Enakta Storage. No file copy. <200ms activation. 20x+ faster first-token latency versus conventional reload.
Blue/green model deploys with automatic rollback on quality regression. Session affinity preserved across pool migrations. vLLM and TGI plugin integration.
HBM → CPU DRAM → Enakta Storage cache tiering maximizes effective context window. RDMA-loaded LoRA adapters enable per-request personalization without engine restarts.
The Enakta Storage Platform is built on DAOS (Distributed Asynchronous Object Storage), the open-source engine that dominates the IO500 global benchmark. We make it production-ready for AI.
Production-hardened bare-metal provisioning and sub-second model activation. vLLM/TGI compatibility. 8,000+ lines, 220+ automated tests.
Enakta Recall: native RAG with tiered embedding retrieval. Enakta Swarm: shared KV cache for multi-agent state coordination.
Sharded media checkpoints, continual fine-tuning, and upstream data pipeline acceleration.
The Enakta Labs AI Platform is currently in limited closed beta. If you're running bare-metal GPU infrastructure and want early access, we'd love to hear from you.