Enterprise
The Vidman AI stack, installed inside your infrastructure — your data center or your cloud.
The OpenAI-compatible endpoint, the full catalog and adaptive routing — on hardware you own. Inference and fine-tuning never leave your boundary; running the stack is our job.
The models worth building on
Enterprise
Enterprise-grade. Out of the box.
Compliance, control, and confidence — built in from day one, not bolted on.
Forward deployed
Our engineers work alongside yours — designing the workload, integrating the systems, and staying until you are live. Not a handoff.
- A dedicated engineer from day one
- Joint design and build
- Ongoing accuracy and cost tuning
- Production support, SLA-backed
Deployment flexibility
Vidman AI deploys where your data already lives: your cloud account, your data centre, or a hybrid of both. The endpoint does not change.
- Private cloud, on-premise, or hybrid
- Air-gapped deployment available
- Bring your own model, or use the catalog
- One OpenAI-compatible API — swap without rewriting
- Fine-tuned weights stay yours, and exportable
Security and governance
Zero retention of prompts and completions — they are never stored and never trained on. Separately, every administrative action carries a full audit trail, so your risk team can see who did what.
- Zero logs, zero data retention
- Role-based access control
- Audit trail on administrative actions
- SOC 2 Type II, ISO 27001, DPDP compliant
- SOC 2 Type II
- ISO 27001
- DPDP compliant
- Role-based access
- Audit trail
- Built and hosted in India
What you get
Enterprise control, without re-plumbing your platform
Four guarantees, none of them a compromise: the data remains yours, your developers keep a single API, the operations burden lands on us — and every checkpoint you train belongs to you.
How a deployment actually goes
01
Bring the capacity you already have
GPUs you already hold, or capacity you procure in your cloud or data center of choice. The cluster stays yours — your account, your nodes, your network policy.
02
We install Vidman AI inside it
The serving stack deploys into your cluster under a dedicated, revocable setup credential, and every runtime component is scoped down to its own identity.
03
We validate it with you
GPU readiness, endpoint reachability, routing and autoscaling are all checked alongside your team before any production traffic reaches the cluster.
04
Production traffic flows
Your applications keep calling the OpenAI-compatible API they already use. Inference and fine-tuning run inside your boundary; we operate the stack day to day.
What teams ask before the first call
Where do inference and training actually happen?+
Inside your environment — your cloud account or your data center. The stack is installed into Kubernetes infrastructure you own, and request handling plus fine-tuning runs stay within your network boundary.
Is this the same API as the managed platform?+
Yes — one OpenAI-compatible endpoint, the same catalog, and Vidman AI Adaptive routing across your on-prem deployment and our managed capacity. Anything written against one runs against the other.
Who runs the deployment day to day?+
Vidman AI does: model deployment lifecycle, upgrades, GPU health monitoring, autoscaling and observability. Your team keeps the environment, the hardware and the network policy.
And fine-tuning?+
It runs on dedicated GPUs billed by the second, and the checkpoint is a file you hold — export it and serve it inside your deployment or anywhere else. Same training product, same ownership.
What happens when traffic outgrows the cluster?+
Hybrid capacity is on the table: eligible workloads can overflow to Vidman AI-managed capacity through spikes, or while your own GPUs are expanded or remediated. Which workloads may overflow, when, and how routing behaves are agreed with your team up front.
What does it take to get started?+
A Kubernetes cluster with NVIDIA GPU nodes, network access that lets us manage the stack, and a conversation with our team about your environment. We confirm fit, then install and validate with you.
Point us at your environment.
Tell us where inference and training must run — a cloud account, a data center, or GPU capacity you already hold — and we will confirm fit, install, and validate alongside your team.
One OpenAI-compatible endpoint · Adaptive routing included · The operations are on us