Deploy full AI capabilities in your own data center. Data stays on-premise, millisecond inference, full control — meeting the strictest compliance for finance, healthcare, government and other regulated industries.
Private AI infrastructure, ready to use from hardware to platform to models
All models and compute deployed in the client's own data center, zero data leaving premises, meeting compliance for finance/healthcare/government regulated industries.
On-prem deployment eliminates public-network latency, 3-5x faster inference, supports high-concurrency real-time inference.
Fine-tuning on private data, continuously improving model quality, knowledge assets fully in your hands.
Supports national crypto algorithms, audit logs, permission isolation, MLPS Level 3 certified, end-to-end encryption.
From single A100 to multi-region H200/B300 clusters, scale monthly, reserve dedicated capacity.
OEM engineers on-site or remote, 99.9% SLA, 2-hour emergency response, 7×24 operations.
Built on the most mature GPU infrastructure and inference acceleration frameworks, fully compatible with mainstream AI frameworks and model formats, migrate smoothly without changing existing workflows.
Already deployed at leading clients across industries, meeting AI deployment needs under varied regulatory environments
Private risk-control models, transaction data never leaves, meets banking regulator data-security requirements.
Local medical LLM deployment, zero patient-data leakage, 60% faster diagnostic assistance.
Factory edge compute coordinated with central cloud, self-trained predictive-maintenance models, 72-hour early fault warning.
Private document-writing and policy-QA LLM, compliant with government data-security regulations.
Standardized delivery, average 15 days from assessment to launch
Assess compute needs, compliance and network, deliver a requirement analysis report
Deliver deployment architecture, security plan and schedule, confirm pricing
GPU servers arrive, racked, networked, infrastructure prepared
Install XABLE platform, deploy models, integration testing with existing systems
Functional acceptance, performance stress test, ops handover, go live
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