The mandatory control plane required to govern durable AI systems.
Grid OS provides the mandatory control plane required to move AI beyond the demo. Every environment starts here to ensure durable, auditable operations.
Start with Grid OS, add practical execution capacity, and expand spend only when real workflows justify it. EngineGrids keeps price tied to the work your business actually runs.
Every EngineGrids launch starts with Grid OS. Build on a deterministic platform where you only add capacity as your workflows earn it, protecting your business from pilot waste and hidden technical debt.
Grid OS provides the mandatory control plane required to move AI beyond the demo. Every environment starts here to ensure durable, auditable operations.
Pulse services cover CPU-backed automations, routing, reminders, service handoffs, and recurring work that does not need GPU capacity. GPU services are available when outcomes require dedicated execution.
No hidden costs or integration debt. Start with a practical first bundle, then move into higher-capacity Grid OS, CPU, GPU, or managed model usage only when the work earns it.
For revenue protection, support triage, and operational handoffs, Spark Grid plus Pulse Standard provides a durable operating home for your first AI win.
Start with Spark or Surge when inference-heavy tasks or high-concurrency swarms are part of the plan. Build on deterministic GPU infrastructure.
Move into Flow or Apex for pre-production environments and enterprise-scale operations. Turn AI into a durable, auditable company asset.
Launch your first AI win on a foundation built to last. This bundle gives your team a governed operating home and dependable CPU execution for production-ready work.
A durable operating home for dev, test, and the first real workflow you want to keep.
Deterministic CPU execution for everyday agent workflows and operational follow-through.
Add managed model usage only when your workflow needs EngineGrids to carry inference.
Every environment starts with the operating layer required to run AI systems your team can inspect and keep.
Pulse services cover routing, service handoffs, reminders, recurring work, and practical AI operations.
Choose GPU capacity when production outcomes require heavier inference, stronger isolation, or specialized workloads.
Add managed model usage when your workflow needs EngineGrids to carry inference, not before.
Move beyond disposable experiments by matching platform, CPU, GPU, and model spend to the work your business is ready to operate.
Grid OS provides the operating home every EngineGrids launch needs.
Pulse services cover everyday automations, routing, reminders, and service handoffs.
Spark, Surge, Flow, and Apex capacity support prototype, production, high-memory, and enterprise workloads.
Keep spend tied to systems your business actually runs instead of buying a giant platform before one workflow works.
Grid OS, CPU, GPU, and managed model usage are priced separately so teams can match spend to real operating needs.
Start with Grid OS. Keep CPU, GPU, and Model Usage separate so spend follows the work your team is actually operating.
Mandatory foundation
Grid OS is the operating foundation for every EngineGrids environment. Start here, then add the execution capacity your first workflow actually needs.
| Name | API name | Best fit | Hourly price | Monthly price | Billing |
|---|---|---|---|---|---|
Lowest cost | Experimental and dev grids on interruptible spot capacity | $0.016756 | $12.24 | ||
Best first launch | Dev, test, and the first real workflow you want to keep | $0.081451 | $59.50 | ||
Growing teams | Growing teams and moderate agent volume | $0.162902 | $119 | ||
Pre-production | Stage, pre-production, and high-concurrency work | $0.325804 | $238 | ||
Maximum headroom | Production-scale systems and enterprise growth | $0.698152 | $510 |
A common first launch pairs Spark Grid with Pulse Standard, then adds managed model usage only when the workflow needs EngineGrids to carry inference.
A durable operating home for dev, test, and the first real workflow you want to keep.
Deterministic CPU execution for everyday agent workflows and operational follow-through.
Add managed model usage only when your workflow needs EngineGrids to carry inference.
Open the portal, start with one useful workflow, and add capacity as your systems prove they are worth expanding.