Token Factory
Training, fine-tuning, and inference delivered as governed, metered model services through a single API. This is where power becomes product.
Power to intelligence infrastructure
One accountable path from megawatts to production AI: modular data centers, elastic GPU cloud, and the TokenFactory platform.
3 MW modular AIDC / elastic GPU cloud / one API for every model
AI demand now grows faster than infrastructure delivery. GPUs are only one part of the challenge: production AI also needs suitable power, high-density cooling, networking, storage, approvals, security, and round-the-clock operations, all aligned to the same service date. Cooma closes the gap between announced capacity and capacity you can actually run.
Training, fine-tuning, and inference delivered as governed, metered model services through a single API. This is where power becomes product.
Elastic and reserved GPU capacity with scheduling, storage, security, and 24/7 operations built in from day one.
Factory-built 3 MW modules with direct liquid cooling and battery-backed power, deployed as single units or scaled into multi-module campuses.
Each stage is accountable on its own, and to the layer above it: one contract, one service date, and acceptance built on measurable evidence.
TokenFactory turns GPU capacity into production-grade model services: training, fine-tuning, evaluation, and inference, delivered as metered output rather than raw GPU rentals. One integration covers frontier, domestic, and multimodal models.
Tokens here are AI inference output, not cryptocurrency.
1{
2 "model": "gpt-5.6-sol",
3 "messages": [{ "role": "user", "content": "Summarize this contract." }],
4 "stream": true
5}
The Cooma GPU cloud turns AIDC capacity into consumable compute. Start on demand, reserve for persistent workloads, or isolate entirely within private deployment nodes.
Launch training, inference, and batch jobs in minutes. Instances come with scheduling, storage, and networking preconfigured, and you pay only while they run.
Guaranteed allocation for persistent workloads, with cluster, storage, and scheduling operated around your service levels.
Isolated compute for regulated and sovereign requirements, where data stays local and residency is provable.
Concurrency follows demand, from quiet overnight batches to product-launch peaks, without re-architecture.
Workloads fail over between regions automatically, with full-chain logging for every request and route.
Monitoring, patching, and capacity planning are handled by the operations layer, so your team ships product instead of running infrastructure.
Conventional data centers are slow to build and hard to reshape. Cooma Modular AIDC is an integrated, containerized platform: modules are prefabricated in the factory and delivered to site, engineered for liquid-cooled, high-density AI compute rather than retrofitted low-density halls.
A reference design, with each deployment sized to its project, from single modules to multi-module campuses.
Integrated liquid loops designed for modern high-density accelerators, not adapted air halls.
Distribution and energy storage engineered for grid disturbance and sustained uptime.
Power, cooling, batteries, controls, security, and operations, co-engineered as one system.
Sited where it makes sense. Every deployment is configured for its geography, workload, and regulatory environment, while keeping a common engineering core. Site, climate, market: starting in Australia, designed to replicate.
Qualify available power, planning and approval paths, fiber connectivity, logistics, and operating conditions before major capital is committed.
Factory-prefabricated modules integrating high-density power, direct liquid cooling, energy resilience, controls, and physical security.
One unified delivery plan aligns factory testing, site installation, systems integration, and operational acceptance.
Continuous monitoring, liquid-cooling operations, remote hands support, maintenance, and service reporting.
Deploy your own GPU systems or partner-financed capacity, with dedicated clusters as demand qualifies.
Confirm site, available power, approval paths, connectivity, and customer requirements.
Adapt the reference architecture to the compute platform, availability targets, and local conditions.
Coordinate factory integration, site engineering, deployment, and commissioning.
Monitor and maintain to agreed service levels, with verifiable operating records.
Add the next module only when power, demand, and commercial thresholds support it.
Site, power, cooling, commissioning, and operations run under a single responsibility.
A proven architecture reused per project, removing avoidable redesign.
Where conditions allow, factory integration and site engineering advance in parallel.
Built for high-density accelerators from first principles, not converted legacy halls.
The next module is added only when qualified power and contracted demand support it.
Operations are anchored to verifiable acceptance criteria and service evidence.
Seven capabilities organized in three layers. Resources keep it stable, the platform keeps it governed, and a single API keeps it simple.
One unified entry point for chat, generation, knowledge retrieval, function calling, and embeddings. Low latency at high concurrency, ready for production on day one.
Language, embedding, image, video, and industry models behind one protocol. Switch freely without re-integration.
Isolated workspaces with their own keys, permissions, quotas, logs, and bills, managed per project and team.
Usage-based pricing with tiered discounts and project-level split billing. Every call is traceable to a cost.
Fine-tuning, quantization, caching, and acceleration tuned to your scenarios, improving quality while cutting long-run cost.
Local deployment and private model hosting for data security, compliance, and dedicated performance, with dedicated operations.
Training, inference, and batch capacity on demand, backing high concurrency and custom models with elastic expansion.
Frontier, domestic, and multimodal models behind a unified protocol, cutting selection, migration, and maintenance cost. Rankings reflect current platform call volume.
Long context, complex reasoning
Code and agents
General, ecosystem
Multimodal, science
Code, value
Long context, knowledge bases
Enterprise applications
Multimodal, Chinese
Demand index is indicative of platform call volume trends.
From GPU to token, self-operated technology and enterprise governance keep every call stable, transparent, and scalable.
Load, latency, capacity, health, and cost are weighed together, with dynamic routing and failover that switches in seconds.
Tenants, permissions, keys, quotas, audit trails, billing, and risk control, covered end to end.
Infrastructure and model operations are optimized as one path, enabling customization and fast response.
Standardized calls across providers remove duplicate development and migration cost.
Public cloud, brand partnership under your own domain, or fully private deployment.
Pay for what you use, while cost-aware scheduling continuously reduces long-run spend.
Stability, cost, compliance, and delivery requirements differ by team. TokenFactory adapts from standard API access to fully private deployment.
01Peak traffic stalls inference interfaces
02Maintaining several vendor APIs is expensive
03Team usage and budgets are hard to track
01One unified model API, integrated once
02Intelligent scheduling with pressure absorption and failover
03Project-level permissions, quotas, and billing
Stable support for AI customer service, assistants, knowledge bases, and SaaS AI features.
01Funding and engineering resources are limited
02Model experimentation means constant switching
03No capacity to run platform operations
01Out-of-the-box cloud service
02Free model switching on one protocol
03Transparent usage-based token billing
Lower cost from prototype through testing to commercial launch.
01Strict data security and compliance demands
02Critical workloads cannot tolerate interruption
03Operations must be fully auditable
01Private deployment with isolated compute
02Multi-node failover and high availability
03Tiered permissions with full-chain audit
Meets classified knowledge bases, intelligent approval, and financial risk control.
01Multi-model experiments are cumbersome to switch
02Batch inference hits rate limits
03Experiment records are hard to trace
01Unified multi-model calling and comparison
02Elastic concurrency that scales on demand
03Complete call logs and billing archives
Faster evaluation and research, with less idle capacity spend.
01No in-house compute or R&D resources
02Hard to build an independent brand
03Billing and customer systems incomplete
01Your own brand, domain, and tenant
02Separate keys and revenue-split billing
03Ongoing platform operations support
Launch your own AI inference service and focus on customers.
01Text, image, and video tools are scattered
02Batch production lacks concurrency
03Content costs are hard to control
01Full multimodal model aggregation
02One interface and one bill
03High-concurrency batch generation
An integrated production pipeline for creative and media teams.
From application integration down to model and compute resources, every layer carries its own security, scheduling, governance, and failover capability.
Cooma builds the layer between available power and production-ready AI compute. Combining modular engineering, managed GPU capacity, and model operations, we help customers deploy AI services at the scale and location their workloads require. The company is currently building its reference platform, project pipeline, and delivery ecosystem.
Persistent or sensitive AI workloads that need accountable delivery and measurable service evidence.
Teams moving from development to production without carrying an infrastructure operations burden.
Experimentation and evaluation across many models, with elastic concurrency and traceable records.
Data residency, isolation, and auditable operations as defaults, not add-ons.
Operators seeking an Australian deployment node with proven infrastructure underneath.
Owners of suitable power seeking to turn reliable supply into digital productivity.
From independent developers to growing enterprises, stable service and engineering support accompany every deployment.
“One interface ended our multi-vendor maintenance. Model switching and product iteration both sped up.
“Stability through traffic peaks improved noticeably, and usage and cost are traceable per project.
“From model selection to production launch, support stayed with us the whole way. A small team shipped AI.
Ready when you are
Whether you are validating an AI idea or running enterprise workloads, we provide the right models, stable services, and sustained engineering support.
Start a Conversation ↗ We engage a limited number of customers, sites, and energy partners, and respond selectively. Tell us your organization, location, and the workloads you need to run.