Deploy state-of-the-art AI inside your own environment — on-premises or dedicated private cloud — with complete data sovereignty and zero public-cloud compromise.
Talk to an Expert Why Go Private?Public AI APIs are convenient — but they come with strings attached. Data sent to third-party models can be retained, used for retraining, or exposed in a breach. For organizations in regulated industries or handling sensitive IP, private deployment isn't optional: it's essential.
Every prompt, completion, and training sample stays within your network perimeter. No telemetry. No third-party data pipelines. Full audit trail under your control.
Meet HIPAA, SOC 2, GDPR, PCI-DSS, and sector-specific regulations without wrestling with cloud provider shared-responsibility models.
Token-based API pricing scales poorly with volume. Private deployment turns per-query costs into flat infrastructure — often 60–80% cheaper at enterprise scale.
Choose the model, version, and configuration. Pin weights, run evaluations, and roll back — without waiting for a vendor's release cycle.
From a single inference endpoint to a multi-cluster training and serving platform, DynaCloud designs private AI infrastructure that fits your workload — not the other way around.
Turnkey NVIDIA H100 / H200 inference clusters with vLLM, TensorRT-LLM, or custom serving stacks. Sub-100ms p99 latency for production workloads.
Full fine-tuning, LoRA / QLoRA, and RLHF pipelines on your proprietary data. We handle distributed training across multi-node GPU clusters.
Retrieval-augmented generation pipelines connected to your document stores, databases, and internal APIs — with semantic search and real-time indexing.
Multi-agent orchestration for complex enterprise tasks: document processing, code generation, customer support, and research automation.
Centralized API gateway with rate limiting, user authentication, usage logging, and content filtering — all on-premises.
Real-time dashboards for throughput, latency, GPU utilization, and model quality metrics — with alerting and automated scaling policies.
We meet you where your infrastructure is — whether that's your own data center, our colocation facility, or a hybrid of both.
We design, procure, and deploy a full GPU cluster in your facility. You own the hardware. We configure and hand it over with full documentation and training.
Your hardware in our Tier III+ Vancouver data center. Physical and logical isolation, with direct cross-connect to your network or major cloud providers.
Split workloads intelligently — training in colo, inference on-prem, with encrypted data replication and unified management plane.
Full managed private AI platform: we handle hardware, OS, model updates, and scaling — you consume an API that never touches a public endpoint.
We work with the leading open-weight foundation models and can integrate with any model that fits your use case — including your own custom-trained weights.
Llama 3.1, 3.2, and 3.3 in 8B, 70B, and 405B variants. Instruction-tuned and base models for any task.
Mistral 7B, Mixtral 8x7B, and Mistral Large for efficient inference with strong multilingual and coding performance.
DeepSeek Coder, StarCoder2, and Code Llama for developer productivity, code review, and automated testing pipelines.
Fine-tuned models for legal, medical, financial, and scientific domains — or bring your own weights and we'll operationalize them.
Book a 30-minute architecture call. We'll assess your use case, data environment, and compliance requirements — and propose a deployment that fits your budget and timeline.
Book a Discovery Call