Galatine Technologies designs, deploys, and operates private LLM and AI server clusters in our ISO 27001, NIST 800-53, and SOC 2 compliant data center. No shared tenancy. No vendor lock-in. No per-token surprise bills. Just dedicated GPU capacity that runs your workloads under your control — paired with the data engineering and model training expertise to keep it productive.
Most organizations start out renting AI from the big cloud providers because it's fast — until the bill arrives, the audit hits, or a model update breaks something. Having your own dedicated servers removes all three risks.
Your data stays on your own dedicated servers. Nobody else trains on it, nobody quietly keeps copies, and it never moves anywhere you didn't approve.
You pay a set price for your servers instead of paying per word processed. For steady, heavy use, that typically works out 40-70% cheaper than the big cloud providers, with no surprise bills.
Once your AI works the way you want, it stays that way. No vendor quietly swapping the model out from under you and changing how it behaves.
Your servers are yours alone, so you're never waiting in line behind someone else's workload. Response times stay fast and consistent, even at the busiest moments.
Hardware, networking, security, and the human expertise that makes AI actually useful, all delivered by one team, so you never have to juggle four different vendors.
Top-tier AI hardware (H100, A100, and L40S), dedicated entirely to you and sized to your needs, from a few machines to multiple racks.
Most "AI problems" are really data problems. Our engineers clean up, organize, and prepare your information into the well-structured training material your models actually need.
We handle every stage of teaching an AI model on your own hardware, whether we start from a proven public model or one you already have.
Real experts (doctors, lawyers, engineers, PhDs) teach and stress-test your models, at a fraction of what the big labeling marketplaces charge.
The big cloud AI services are great for getting started. But once you're relying on them heavily every day, paying by the word gets expensive fast. Below is a realistic side-by-side for a mid-size company's workload.
Figures shown are representative for a 50M token/day mixed inference + fine-tuning workload on a Llama-3.1-70B class model. Actual savings depend on model size, throughput profile, and contract length. We provide a detailed capacity plan and TCO model after a 30-minute discovery call.
Our data center is independently certified against major security standards, and everything we set up for you inherits those protections. That makes your own audits simpler, not harder.
Annual third-party certification of the full ISMS, covering risk treatment, access control, cryptography, supplier relationships, and incident response across physical and logical scope.
Controls aligned to the moderate impact baseline, with documented inheritance available to support your own ATO process or FedRAMP authorization package.
Independent attestation across Security, Availability, Confidentiality, and Processing Integrity, with annual reports available under NDA for procurement and vendor risk reviews.
Most clients move from first call to live inference inside six weeks. Larger training programs follow a phased rollout that keeps validation tight at every step.
One call to understand throughput, latency, model size, and compliance scope. We come back with a sized capacity plan, total cost of ownership model, and shortlist of base models that fit the workload.
Our data engineers walk the existing pipelines, identify quality and governance gaps, and ship the ingestion, cleaning, deduplication, and labeling infrastructure that your model training will rely on.
Hardware is allocated in your single-tenant slice, network segmentation and key management are wired up, and your security team gets read access to the control plane for review before any workload runs.
Pre-training, SFT, RLHF, or DPO — whichever shape your problem needs — runs on the dedicated cluster with versioned checkpoints and held-out evaluation against your domain benchmarks.
We hand off (or continue to operate) the serving stack with autoscaling, observability, on-call coverage, and quarterly model refreshes against your latest data.
Dedicated LLM and AI server clusters, built on NVIDIA H100, A100, and L40S GPUs and hosted in Galatine Technologies' ISO 27001, NIST 800-53, and SOC 2 compliant data center, used only by you. Private inference, model training and fine-tuning, and data engineering all run on hardware under your control, with no shared tenancy, no vendor lock-in, and no per-token bills.
You pay a set price for dedicated servers instead of paying per word processed. For steady, heavy daily use, that typically works out 40 to 70 percent cheaper than the big cloud AI providers, with predictable bills and no surprise overages.
Yes. The data center is independently certified against ISO 27001, NIST 800-53, and SOC 2, is FedRAMP-aligned and HIPAA-ready, and everything we set up for you inherits those protections. Your data stays on your own dedicated servers and never moves anywhere you didn't approve.
Most clients move from first call to live inference inside six weeks; larger training programs follow a phased rollout that keeps validation tight at each stage. Tell us the model you want to run, the throughput you expect, and the compliance boundary you sit inside, and we'll return a sized plan with total cost of ownership and a timeline within two business days.
Tell us what model you want to run, how much throughput you expect, and what compliance boundary you sit inside. We'll send back a sized plan with TCO and a deployment timeline within two business days.