Architecture · Verified Product Boundary

How ToggleLogic Fits

A decision component between your workloads and approved AI resources.

ToggleLogic Intelligence receives a workload description and the policy and candidate evidence implemented for a deployment. Before execution, it recommends an eligible configured resource—or returns an explicit escalation—and produces structured evidence for review.

1. Workload requirement

The consuming application supplies the work to evaluate. Intelligence classifies the required capability tier and any implemented execution-surface requirement.

2. Candidate boundary

The deployment supplies its configured providers and model candidates. Unavailable, unconfigured, quarantined, or ineligible candidates are excluded.

3. Decision evidence

Capability-tier evidence, modeled cost, provider state, owner pins, execution-surface requirements, and deployment policy inform the recommendation.

4. Recommendation or escalation

Intelligence returns a recommended configured model when one qualifies. If none does, it can decline to recommend rather than invent a safe route.

5. Shadow evaluation

In shadow mode, the full recommendation is recorded while the host retains its existing selected route. Nothing changes until authorized promotion.

6. Agreed integration boundary

ToggleLogic is currently proven through the OpenClaw plugin seam inside SAM. Additional runtime interfaces, packaging, and support scope are defined during licensing evaluation.

Current Intelligence does not claim automatic data-sensitivity classification, residency-aware routing, universal latency optimization, native CRM or ERP connectors, or a guaranteed savings or security result. Those requirements must be implemented and verified for the licensed deployment before they become product claims.

Explore ToggleLogic Intelligence →

Prove in shadow mode · Promote under named authority