Applied AI systems
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The workflowcomes first.

We design, integrate, and govern AI systems inside defined workflows, with evaluation and human control built in.

Show us the workflow.Prepare a local, non-confidential brief; nothing is sent.
See how we work
A workflow moves from noisy input to reviewed actionInputs converge on a human evaluation gate, then continue into approved action, exception, fallback, and rollback paths.NOISY INPUTEVALUATEAPPROVED ACTIONEXCEPTIONFALLBACKROLLBACK REMAINS OPENA workflow moves from noisy input to reviewed action in a vertical mobile layoutInputs converge on a human evaluation gate, then continue into approved action, exception, fallback, and rollback paths.NOISY INPUTEVALUATEAPPROVED ACTIONEXCEPTIONFALLBACKROLLBACKREMAINS OPEN
The system starts with a defined workflow, evaluates a bounded intervention, keeps human review visible, and preserves exception, fallback, and rollback paths.

Intelligence that enters the work.

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.

Abstract material study showing many signal paths reaching a bright human-control gate and separating into bounded routes

Put intelligence on the critical path.

Start with one consequential bottleneck. Define the current path, the intervention, the review gate, and what happens when the system is uncertain or wrong.

Entry
A defined workflow or decision with a measurable bottleneck.
Boundary
A bounded launch, approved transfer or operating model, or a clear stop decision.
Assess the workflow

Systems shaped by the work.

The intervention follows the constraint. Sometimes that means a model. Sometimes it means rules, retrieval, review, or a simpler piece of software.

Decision support

Bring evidence, uncertainty, and review into a defined decision without hiding the final judgment.

Document and knowledge intelligence

Route information through source-aware retrieval, extraction, review, and traceable output.

Workflow agents

Use bounded tool access and explicit approvals where multi-step execution is justified.

Forecasting and optimization

Join predictions to the constraints, decisions, and feedback loops that make them useful.

Human review and exceptions

Design the queue, escalation, evidence, and reversal path around critical actions.

Explore the system types

A method with stopping points.

Five moves. Each leaves inspectable evidence; expansion depends on what it shows.

  1. Identify

    Define the decision, current path, failure modes, owners, data access, and acceptance criteria.

    • Workflow map
    • Baseline
    • Acceptance criteria
  2. Design

    Specify deterministic logic, AI behavior, permissions, evaluation, review gates, fallback, and economics.

    • System design
    • Evaluation set
    • Control matrix
  3. Integrate

    Connect identities, permissions, source systems, tools, instrumentation, and reversible actions.

    • Integrated system
    • Permission model
    • Operating record
  4. Assure

    Evaluate quality, edge cases, security, latency, cost, misuse, escalation, oversight, and rollback.

    • Test report
    • Launch boundary
    • Rollback plan
  5. Improve

    Monitor outcomes, adoption, exceptions, latency, cost, and failed or escalated cases.

    • Monitoring plan
    • Exception review
    • Change record
Show us the workflow.Prepare a local, non-confidential brief; nothing is sent.
Read the full method

The model is one layer.

Sources and permissions enter orchestration. Evaluation and human review govern the action. The operating record preserves what happened and the way back.

Layers of a bounded production AI system
  1. SourcesSystems of record, documents, events
  2. IdentityUsers, roles, permissions, boundaries
  3. OrchestrationRules, models, tools, state
  4. EvaluationAcceptance criteria, evaluation set, edge cases, cost
  5. Human reviewEvidence, approve, correct, reject, escalate
  6. Operating recordLogs, monitoring, fallback, rollback

One decision / intended control path

  1. Review

    An accountable reviewer sees the source, identity, permission, acceptance result, and prior state.

  2. Decide

    Approve, correct, reject, or escalate.

  3. Reverse

    Record and monitor the decision. On exception, use fallback or restore the prior state through rollback.

Inspect the control model

Show us where the work gets stuck.

Bring 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.