AI Token Factory | Turn GPU Inference into Monetizable AI Services | Rafay

Transform GPU Capacity into Monetizable AI Services with Token Factory

Most organizations operate GPU infrastructure. Few can transform it into a monetizable AI service. The Rafay Platform's AI Token Factory capability adds a governed, token-metered service layer on top of your existing infrastructure—turning inference into revenue-generating AI services. Start a conversation with us to understand how the Rafay team can elevate your AI infrastructure with this cutting-edge capability.

Token Factory FAQs

An AI Token Factory transforms inference infrastructure into token-based AI services, governed and monetized at the unit of consumption. It shifts organizations from managing compute capacity to delivering measurable AI outcomes as scalable, revenue-generating services.

What counts as a node?

A node is a physical or virtual server/machine.

Do you have any volume discounts?

Yes! As the number of nodes increases the price per cluster or per node decreases.

What about short-lived or ephemeral clusters?

Our customers love to experiment, and we don’t ding them for it. We don’t charge for node count spikes but look at the running average of nodes in use when calculating usage.

Is there a difference between production and non-production pricing?

The management overhead for helping our customers operate dev vs prod clusters is effectively the same, so we treat all nodes the same.

What if I use more nodes than I’ve licensed?

Rafay has a true-up forward policy, meaning that we don’t carry out chargebacks for scenarios where the consumption in a completed billing cycle exceeded the licensed count. If the new steady-state number of nodes is expected to be higher, our customer success team will discuss the situation with you, and take steps to adjust billing accordingly for the next billing cycle.

How much does Enterprise Support (24x7x365) cost?

Enterprise Support is available at an additional fee equaling 20% of the cluster or node subscription.

Do you have EDU or GOV discounts?

Yes, please contact sales for more information about discounts for educational institutions and government agencies.

What is a token in AI?

A token in AI is a unit of text that a language model processes. Instead of reading full words or sentences, AI models break text into smaller pieces called tokens, which can be whole words, parts of words, punctuation, or symbols. Large language models generate responses one token at a time, and token counts determine context limits, performance, and cost.

How does LLM token generation work?

LLM token generation works by tokenizing an input prompt, running it through a trained neural network, and predicting the next most probable token. This process repeats sequentially until the full response is produced. Each new token is influenced by the tokens that came before it, which allows models to generate coherent text.

What is an AI token factory?

An AI Token Factory is the operating layer that transforms GPU infrastructure into governed, consumable AI services. Instead of exposing raw GPUs or unmanaged clusters, organizations deliver production-ready model APIs that are:

Serverless inference is how models are delivered. A Token Factory is how they are scaled, controlled, and turned into repeatable services.

What role does Rafay play in AI factories? Rafay provides the control plane for AI factories, handling orchestration, multi-tenancy, governance, and self-service access to AI infrastructure across cloud, on-prem, and sovereign environments.

From endpoint to billing data in minutes

Turn GPU capacity into a token-driven revenue stream

AI consumption is shifting fast. OpenClaw is driving real, immediate demand — and that usage is already generating revenue.

Token-Based Consumption Economics

Service-level Multi-Tenancy & Isolation

Elastic, Demand-Based Scaling

Integrated, Billing-Ready Metering

Why Choose Rafay for AI Token Factory?

Rafay provides the operational and economic control plane required to deliver inference as a governed, scalable, revenue-generating AI service.

OpenAI-Compatible Inference APIs

Token-Level Usage Metering

Shared and Dedicated Endpoints

Elastic, Policy-Driven Scaling

Flexible Billing Models

The Shift from GPU Billing to AI Services

Traditional GPU billing is infrastructure-centric and hard to align with business value. AI Token Factory changes the economic model.

Typical Process Before vs. After

  1. Billed by compute time
    Process with Rafay: Token-metered consumption billing
  2. Hard to align with business value
    Process with Rafay: Direct alignment to AI usage and value
  3. Limited consumption visibility
    Process with Rafay: Execute a dry run.
  4. No native chargeback
    Process with Rafay: Built-in chargeback and showback
  5. Overprovisioning inefficiency
    Process with Rafay: Auto-scaling eliminates over-provisioning