Private & Offline LLMs
Your own LLM, inside your own perimeter.
Fine-tuned open models served in your VPC, on-premise or fully air-gapped — zero data egress, full residency control, and lower cost than API calls.
Fine-tuned open models served in your VPC, on-premise or fully air-gapped — zero data egress, full residency control, and lower cost than API calls.
A complete self-hosted stack — models, serving, security and operations — with the economics of owning instead of renting.
On-premise, VPC or fully air-gapped — the model runs where your data already lives, with zero egress.
INT4 / INT8 quantized models cut memory and cost while keeping quality — more throughput per GPU.
LoRA and QLoRA adapters tune open models to your domain — trained on your data, kept as your asset.
An inference gateway with RBAC, rate limiting and audit logging — every request accounted for.
In-VPC inference with autoscaling — no internet round-trip, no rate limits you don't set yourself.
Blue-green rollouts and instant rollback — model upgrades on your schedule, never a vendor's.
Self-hosted, quantized models running in your VPC or data center — behind an inference gateway with RBAC and full observability.
All traffic enters through a secure inference gateway that enforces who can ask what, and logs everything.
Quantized open models run on vLLM with continuous batching — high throughput and low latency on your own compute.
RAG over your internal documents keeps answers accurate — and the knowledge base never leaves the perimeter either.
Autoscaling, monitoring and blue-green upgrades keep the stack healthy — online, in your VPC, or fully air-gapped.
A secure, self-hosted LLM stack — gateway, quantized serving, GPU compute and private data, air-gap capable end to end.
A fixed-scope path from compliance requirements to a model serving inside your perimeter.
We assess your workloads, GPU options and residency requirements, and select the right open model and quantization.
A quantized model serving real queries in your VPC or on-prem environment, benchmarked for latency and cost.
Gateway, monitoring and upgrade process in place — including air-gapped operation where required.
Full case study below — including the RBAC gateway and audit trail that satisfied the compliance team.
Sensitive customer and policy data made public LLM APIs a compliance non-starter, blocking a much-needed internal copilot.
Deployed a quantized (INT4) open-weight model in the client VPC with RAG over policy documents, an RBAC inference gateway and full audit logging.
A secure copilot for 800+ staff with zero data egress and predictable, capex-friendly economics.
Plant engineers lost hours searching SOPs, manuals and maintenance logs — often on air-gapped shop-floor networks.
Built a multi-agent system — retriever, planner, tool-executor — on a self-hosted model, running offline at the plant edge with role-scoped knowledge.
Instant, grounded SOP guidance with no cloud dependency and controlled model upgrades.
Tell us your residency requirements and workloads — we'll return a model, GPU and cost plan in days.