Decision support
Bring evidence, uncertainty, and review into a defined decision without hiding the final judgment.
We design, integrate, and govern AI systems inside defined workflows, with evaluation and human control built in.

A demo can prove a model responds. It does not prove the workflow has changed. The hard work sits in the decision, handoff, permission, exception, and consequence around that response.
sgz.ai starts there. We map the work, define what good means, place human judgment where it matters, and keep the system observable and reversible.

Start with one consequential bottleneck. Define the current path, the intervention, the review gate, and what happens when the system is uncertain or wrong.
The intervention follows the constraint. Sometimes that means a model. Sometimes it means rules, retrieval, review, or a simpler piece of software.
Bring evidence, uncertainty, and review into a defined decision without hiding the final judgment.
Route information through source-aware retrieval, extraction, review, and traceable output.
Use bounded tool access and explicit approvals where multi-step execution is justified.
Join predictions to the constraints, decisions, and feedback loops that make them useful.
Design the queue, escalation, evidence, and reversal path around critical actions.
Five moves. Each leaves inspectable evidence; expansion depends on what it shows.
Define the decision, current path, failure modes, owners, data access, and acceptance criteria.
Specify deterministic logic, AI behavior, permissions, evaluation, review gates, fallback, and economics.
Connect identities, permissions, source systems, tools, instrumentation, and reversible actions.
Evaluate quality, edge cases, security, latency, cost, misuse, escalation, oversight, and rollback.
Monitor outcomes, adoption, exceptions, latency, cost, and failed or escalated cases.
Sources and permissions enter orchestration. Evaluation and human review govern the action. The operating record preserves what happened and the way back.
One decision / intended control path
An accountable reviewer sees the source, identity, permission, acceptance result, and prior state.
Approve, correct, reject, or escalate.
Record and monitor the decision. On exception, use fallback or restore the prior state through rollback.
Two practical field notes turn the operating standard into questions your team can answer, challenge, and revise.
Define the bottleneck, evidence, owners, and acceptance criteria before choosing a system.
Open field noteOperating method · Reviewed 2026-07-31Specify the tests, permissions, review, failure behavior, and operating evidence a bounded launch needs.
Open field noteBring the situation, desired change, why now, and what prevents movement. Prepare the brief locally and keep it non-confidential; nothing is sent.
Show us the workflow.Prepare a local, non-confidential brief; nothing is sent.