Support & Maintenance
Keep your private AI healthy, current, and secure.
Cloud, on-prem, or at the edge.
Same model, same governance, same control plane — sized and operated for the environment that fits your security, latency, and cost profile.
- On-prem for full data sovereignty
- Private cloud (AWS · Azure · GCP) for elastic scale
- Edge for offline + low-latency environments
Ongoing model updates, monitoring, evaluation, and support so your deployment stays performant and compliant as your needs — and the model landscape — evolve.
What you get
We design, deploy, and operate private LLM infrastructure for organizations that need full control of the model and the data flowing through it.
From a single pilot to a multi-tenant platform, you get a deployment sized to your hardware, optimized for your models, and operated against the SLA your business actually needs — with handoff or co-operation, your choice.
Common questions
01Where can the platform be deployed?
On-prem inside your data center, in your private cloud (AWS, Azure, or GCP), in air-gapped/offline environments, or on edge hardware. Hybrid setups can route sensitive workloads to private models while still tapping frontier APIs for non-sensitive tasks.
02How do you handle updates?
Models, retrieval indexes, and orchestration are versioned and updated on a cadence you control, with rollback. You decide when, on what cadence, and against what evaluation suite.
03What does ongoing support look like?
We monitor and respond on the SLA you need — from business-hours to 24/7. You can also pair our team with your internal platform engineers for joint operation.
Private AI On Your Terms
Tell us your use case and constraints — on-prem, cloud, or edge — and we'll map a compliant deployment within one business day.
Talk to an AI Expert