1. Capture context
Identify the work, source, requester, current state and required outcome.
OPERATING MODEL
One controlled path from incoming work to measurable outcome.
Governed execution separates interpretation, policy, authority and action so each can be tested and improved independently.
Discuss this workflow →THE OPERATING PRESSURE
Why this matters
When model reasoning and system action are fused together, operations teams cannot see where an error occurred, who had authority or how to recover safely.
CONTROLLED WORKFLOW
What GZP makes visible
Each layer has a clear purpose, boundary and decision owner.
2. Interpret safely
Use the model to structure ambiguity; preserve the original evidence and confidence.
3. Apply policy
Run deterministic validations and decide whether the work may proceed.
4. Retain authority
Pause, approve, reject, amend or recover through an accountable human decision.
CONTROLLED EXECUTION PATHILLUSTRATIVE MODEL
- 01Capture
- 02Interpret
- 03Validate
- 04Authorise
- 05Complete
Rules decide whether work can proceed, pause or enter review.
Material ambiguity and high-risk actions enter a controlled state.
Decision context, action and outcome remain visible.
FIRST COMMERCIAL DECISION
Map an opportunity →The result is not autonomous activity. It is a controlled operating record that links evidence, decision, action and outcome.
ENGAGEMENT PATH
Increase commitment only when the evidence supports it
The commercial path is staged so a buyer can test workflow fit, controls and measurable value before expanding scope.
Example and Opportunity Record
Explore the controlled order example, describe your workflow and save an enquiry. Download a preparation record with your reference and a measure to discuss.
Opportunity Scan, subject to fit
If a deeper review is suitable, agree scope and terms. Establish the baseline, exception pattern, authority model and system boundary before proposing a pilot.
Bounded pilot
Test one agreed path with explicit acceptance measures, exception ownership and controlled permissions.
Production expansion
Extend channels, systems or decision rights only after the operating evidence supports the next boundary.
BUYER FAQ
Questions to resolve before operational AI moves into production
What is governed execution?
Governed execution separates AI interpretation from deterministic policy, human authority and system action. The incoming evidence, model output, validation result, approval, action and outcome remain linked so the workflow can be reviewed and recovered.
How is GZP different from an AI assistant or general-purpose agent?
An assistant normally returns an answer. A general-purpose agent may plan and act across broad tools. GZP starts with one bounded operational workflow, explicit business rules, limited action permissions, named exception owners and measurable acceptance criteria.
What does GZP evaluate before proposing a pilot?
The assessment examines workflow volume, cycle time, manual touches, recurring exceptions, evidence availability, decision authority, system boundaries and the outcome the operating team can verify.
How are timing and commercial scope decided?
GZP does not publish a universal pilot duration or price before the workflow is understood. Scope depends on channels, transaction volume, exception complexity, evidence quality, integration boundaries and agreed acceptance measures.
Can the work start without writing to the ERP?
Yes. A read-first or decision-support scope can establish whether an exception pattern is repeatable and material before any remediation or system-write permission is introduced.
Does governed execution remove human approval?
No. Material ambiguity, high-value actions and policy exceptions can be routed to an accountable person. The objective is to make authority explicit and efficient, not to remove it by default.
DEPLOYMENT FIT
Agree the boundary before granting access.
Use these five gates to scope a deployment. Supported integrations and the responsibility split must be confirmed for the selected environment.
- 01
Workflow
Name one recurring process, its outcome, operating owner and exceptions.
- 02
Data and systems
Identify approved inputs, the authoritative record, providers, interfaces and permitted reads or writes.
- 03
Authority
Agree rules, approval rights, exception ownership and who can pause the workflow.
- 04
Test readiness
Prepare representative cases, non-production access and checks for duplicates, stale data and partial failures.
- 05
Operations
Assign monitoring, reconciliation, incident response and a stop, continue or scale decision.
Customer decisions
Identify process and system owners, approved data, business policies, approval authority and acceptable risk.
GZP scope to confirm
Confirm the supported interfaces, implementation boundary, evidence available and operating support included in the engagement.
Agree together
Record permissions, responsibilities, test criteria, incident escalation and recovery. Allocate each responsibility in the selected deployment.
ILLUSTRATIVE PILOT DESIGN
Studio booking: start with staff-confirmed requests.
A hypothetical example of the method, not a customer case study, available booking service or proven result.
Start with intake
Choose one class or venue. Staff check the authoritative calendar, capacity, buffers and studio policies before confirming a request. AI may draft a reply for review.
Test read-only checks
With approved access, compare availability checks against staff decisions. Define freshness limits and route stale data or conflicts to staff.
Gate each new action
Calendar writes, chat automation, charges or refunds, and timed door credentials each need a selected provider, permission, tests and recovery plan. Keep them staff-operated until their gate passes.
Measure request-to-decision time, staff touches per confirmed booking, conflicts, exception age and failed notices. Agree the baseline and stop conditions before testing. No integration or savings result is assumed.
Explore Service CoordinationTHE OPERATING PRINCIPLE
AI interprets. Rules decide. Humans retain authority.
Every material action needs a visible decision path: what the model understood, what policy allowed, who approved, what system changed and whether the intended outcome was achieved.