AI DECISION CHECKS
Check an AI-generated configuration, allocation or plan against approved, explicitly modeled requirements before an authorized system acts.
Available products. A customer-specific workflow.
CLI · MCP · Headless
Enterprise-agent builders, infrastructure platforms and engineering teams introducing AI-assisted decisions.
A useful implementation has a specific job. The scope is built around your original requirements, environment and acceptance criteria.
Natural-language confidence is not a test of resource limits, compatibility or exclusivity.
Evaluate the supported proposal against a model approved by your team. Return the violated requirements, a checked candidate or an unresolved result instead of relying on confidence alone.
A decision can be valid for an earlier capacity or policy snapshot and wrong for the current one.
Attach the evaluation to the accepted rule and input revision. Recheck a supported revision before it proceeds to the next step.
Simply blocking a decision may not help an operator find a workable alternative.
Where the selected product and model support it, request a corrected candidate or compare alternative scenarios. Keep checking separate from execution authorization.
The final order identifies the selected products, integration work and operating responsibilities. Included components and work are not charged again.
The proposal fields, approved constraints, valid input ranges and required evidence for one defined decision workflow.
Checked, rejected and unresolved outcomes with the relevant failed requirements or proof limitations.
A supported re-planning path evaluated against the same original requirements—not an unreviewed rewrite of the policy.
Integration with the customer-controlled review or execution step, including permissions, spending limits and the operating responsibility.
An assistant suggests placing work on a set of resources. The current allocation limits and eligibility rules must be checked before an operator approves the change.
Explanation only—not a live product run or a claimed customer deployment.Your team supplies the decision schema, rule snapshot and proposed allocation. Modeling accuracy is reviewed separately from solving.
Agree the supported models, execution environment and acceptance measures before committing to the delivery.
Choose the relevant capability.
Not every workflow needs every product.
Use eligible product access for the agreed model. Custom proposal parsing, agent integration, approval controls and managed operation require a defined service scope. No new blanket per-agent fee is implied.
No. It checks explicit supported requirements. Unmodeled requirements, incorrect source data and execution failures need their own controls.
Not by default. The customer separately assigns execution authority, approvals and rollback responsibilities. MCP access is not an unrestricted action grant.
Yes. A scoped integration can record what would pass or fail without changing the production decision path.
UNISOLVE latest supplied inventory expands admitted optional/variable scheduling and logical reasoning. Select the specific input and check before connecting this workflow to an authorized decision process.
Commission the model, integration and acceptance work needed for your task. Existing products stay independently available.
Commission one supported decision model, a scoped conflict analysis and a comparison of permitted repairs.
02 / Scoped customer programCommission a revision-aware workflow that keeps models, assumptions, results and evidence connected as inputs change.
One capability. A connected workflow.
A team to put it into practice.