AI execution.
Under your control.
Bring models, infrastructure, and changing policies into one execution layer. Keep the next action aligned—and the decisions behind it visible.
An early-stage concept, shaped through scoped pilots.
Designed around
the way you run AI.
Rules change.
Your next action should, too.
Permission at the start is only part of the story. numericspace is designed to check the current policy as work starts, retries, moves, and releases a result.
Make policy changes operational.
Carry updated permissions into the next controlled action, with a record of the rule that applied.
Explore the checkpoints ↗ 02 / EXECUTIONPut the right work in the right place.
Evaluate eligible models and workers against the workflow’s permissions, requirements, and budget.
See the execution layer ↗ 03 / EVIDENCEv13local✓Know how the result happened.
Connect decisions, attempts, and reported costs into a workflow record your team can inspect.
Follow the evidence ↗One work order.
A connected record.
Keep the policy version, execution attempts, and cost information together. Review what ran, what was held, and what still needs reconciliation.
Open the execution console ↗Explore sample data in a browser-based simulation.
Quarterly review
job_1042 · document analysis
- Policy at dispatch
- v12 → v13 at release
- Execution route
- Approved local worker
- Provider attempts
- 2 linked attempts
- Cost reconciliation
- Awaiting final usage
Built around the work
you need to govern.
Keep sensitive steps
in approved environments.
Explore local and cloud document analysis with clear transfer boundaries.
↗ AI OPERATIONSKeep retries
within the rules.
Evaluate budgets, permissions, and recovery decisions as conditions change.
↗ DEVELOPER WORKFLOWSSeparate permission to
investigate from deploy.
Recheck the next consequential action before work moves forward.
↗Illustrative pilot scenarios. No customer deployments or measured outcomes are represented.
Start with one workflow.
Make the outcome measurable.
A proposed 4–6 week pilot: one workflow, two execution points, and a clear evaluation.
Plan your pilot →Proposed fixed fee.
Scope and acceptance criteria agreed before kickoff.
What stage is numericspace at?+
numericspace AI Execution Controller is an early-stage product and research concept. This website demonstrates the proposed experience. A pilot would define which capabilities are implemented and evaluated for a specific workflow.
Do I need to move my infrastructure?+
The proposed model connects selected local workers and approved cloud endpoints. A pilot determines which existing environments can be supported. Customers would retain their own provider relationships and pay underlying compute charges separately.
Can a policy change stop work that is already running?+
It can block the next action controlled by the orchestrator. Cancellation of external work depends on provider support, and a request to cancel does not establish that execution stopped. Data already transferred cannot be recalled by changing a policy.
Are auctions part of the first release?+
Auctions and strategic resource allocation are a future research direction. The initial pilot focuses on routing, policy checkpoints, execution records, and evaluation.
Can I try the interface?+
Yes. The interactive demo lets you explore sample workloads, change policies, and export simulated evidence. It does not connect to live workers or spend money.