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GibsonFamily-Owned Sydney Lead Engine · Since 2006
BUILD · AI CONSULTING FOR AUSTRALIAN BUSINESSES
AI consulting for deciding what to automate, test and implement.
Gibson helps you find the workflow problem worth solving, compare AI with simpler options and test the best approach before committing to a full build.
You leave with a clear map of the current work, the expected value, human approvals, risks, test results and the next practical decision. Gibson has taken its own browser telephony workflow into production and has a recruitment workflow in active prototype development.
Last reviewed 3 August 2026 · By Albert Triolo, Founder and Managing Director
PLAIN-LANGUAGE WORKFLOW REVIEWPROBLEM BEFORE TOOL
BUSINESS PROBLEMMANUAL EXCEPTIONS DELAY THE WORK
CURRENT FACTSWORKFLOW, FAILURES AND VOLUME
HUMAN DECISIONSWHAT PEOPLE MUST STILL APPROVE
NEXT STEPFIX, AUTOMATE, TEST OR STOP
What you gain: a practical decision and action plan, even when the right answer is to simplify the process or not build AI at all.
01 · HOW WE WORK
How does Gibson decide whether AI is worth testing?
Gibson maps the current problem, compares AI with simpler options, runs a focused test when useful and records the evidence needed for the next business decision.
- 01Constraint
Name the operating problem before the technology
The brief identifies the delay, error, risk, cost or coordination failure, the people affected and the decision that matters. AI is not assumed to be the answer.
- 02Evidence
Inspect the current workflow and available evidence
Inputs, handoffs, exceptions, systems, volumes and existing attempts are mapped. Sensitive records are not requested through the generic enquiry form.
- 03Control
Define human approvals and unacceptable failure
The workflow names what a person must approve, what the system may suggest or perform, where uncertainty is surfaced and which actions must never happen automatically.
- 04Option
Compare process, automation and AI options
A rule, integration, training change or simpler operating fix may be better than a model. Options are compared against evidence, control, effort and measurable value.
- 05Test
Set clear limits for the assessment or prototype
The test states who will use it, which data and examples are included, what a useful result looks like, how it will be checked and when to stop. Everyone can see that it is still a prototype.
- 06Decision
Decide what the results support
The outcome may be to stop, improve the process, run another focused test or plan production as a separate piece of work. A prototype is never treated as approval to go live.
02 · INSPECT THE WORKFLOW
What happens before Gibson proposes an AI prototype?
Gibson records the problem, current evidence, simpler options and human decisions first. A focused test is proposed only when it can answer a useful business question.
EXAMPLE EVIDENCE-TO-DECISION MAP
Named delay, affected users and decision owner.
Inputs, handoffs, systems, volumes and uncertainty.
Simplest viable paths compared before selection.
Low confidence and exceptions return to a person.
Expected behaviour, evidence and stop conditions.
Production remains a separate operating commitment.
01
Problem risk
Automating an unclear workflow can scale the confusion.
02
Evidence risk
A polished demo can hide weak scenarios and missing data.
03
Control risk
Automation without accountable human ownership is not an operating design.
03 · KNOW WHAT STAGE IT IS IN
What is the difference between an assessment, prototype and live implementation?
An assessment produces a decision and action plan. A prototype tests the riskiest assumptions. A live implementation adds production security, monitoring, ownership and ongoing support.
Evidence before build
Maps the problem, workflow, risks and options. No working product or automation is implied.
A focused learning test
Tests selected examples with agreed data, human checks and stated limits. It is not approved for live business use.
A separate operating commitment
Requires security, reliability, monitoring, access, support, change control and accountable ownership confirmed in writing.
Current workflow map
People, inputs, handovers, delays, exceptions, systems and the decision that matters, shown in one view.
Risk and approval plan
Sensitive data, access, human approvals, unacceptable outcomes, uncertainty and who is responsible.
Prototype test plan
Realistic examples, expected behaviour, useful measures, known limits, reasons to stop and a clear status label.
Decision and action record
What the test supports, what remains unknown, the recommended next step, responsibilities and any separate work needed to go live.
04 · WHAT GIBSON HAS BUILT
See what is a prototype and what is already live.
Gibson's internal register contains one active prototype and one live production workflow. Their status proves practical experience, not that another workflow will achieve the same result, timing or operating profile.
REGISTERED STATUS · WORKING PROTOTYPE
Mr Jobs Recruitment Engine
The internal build register describes document parsing, structured candidate scoring, a voice interview path and an operator portal. Its status is BETA and active development. It is presented as prototype evidence, not a production product or customer outcome.
REGISTERED STATUS · PRODUCTION
Mr Jobs browser telephony
The internal build register describes a browser phone system as live and operational. This shows that Gibson has taken a clearly defined workflow into production, but it does not prove an unverified cost, speed, reliability or commercial result.
WHAT YOU CAN REVIEW
4Workflow map, approval plan, test plan and decision record
These outputs make the proposed problem-solving method and project stage clear before a brief.
They explain the method, not a customer-specific solution or promised result.NEXT PRODUCTION EXAMPLE
OPENA real workflow, test history and operating record
A future example will show a real workflow, representative tests, human approvals, live status, known limits and customer permission.
No generic dashboard or stock AI image fills the gap.05 · IS THIS WORTH TESTING?
Know what must be true before committing to a build.
The first decision is whether an assessment or focused prototype would be useful. Launch timing, platform and ongoing responsibility are confirmed later and separately.
Good fit
- A specific workflow, failure or decision can be named.
- Representative evidence and process owners are available.
- Human approvals, unacceptable outcomes and a useful test can be defined.
Poor fit
- The request begins and ends with wanting an AI agent.
- No owner can explain the current process or approve a changed one.
- A prototype is expected to become production without security, support or operating review.
What Gibson needs
- The current workflow, users, systems, delays, exceptions and existing attempts.
- Available aggregate evidence, data sensitivity and access constraints.
- Required human decisions, success signal, target decision date and accountable owner.
What changes the scope
- Workflow breadth, user groups, systems, integrations and data quality.
- Risk level, permissions, evaluation depth and human-control requirements.
- Prototype fidelity, deployment environment, monitoring, support and production responsibility.
WHAT SHAPES THE QUOTE
Scope problem, facts, approvals, test and ownershipThe written proposal confirms what Gibson will deliver, the project stage, data limits, testing, approvals, launch target, price and responsibilities.
06 · QUESTIONS BEFORE BUILDING
AI consulting questions, answered directly.
These answers keep assessment, prototype and live production clearly separated.
What does an AI consultant do?+
An AI consultant should help define the business problem, understand the current work and available facts, compare simpler options, decide what people must still approve and state what a focused assessment or prototype must prove. Recommending AI before that work puts the tool before the problem.
Is AI the right answer for every workflow problem?+
No. Some problems are better addressed through clearer ownership, process changes, rules, training or a conventional integration. Gibson compares those options before recommending AI automation or a prototype.
What is an AI workflow assessment?+
An AI workflow assessment maps the current process, evidence, constraints, risks, system boundaries and human decisions. It produces an option decision and action plan; it does not claim that a build has occurred or that automation is already approved.
How is an AI prototype different from production?+
An AI prototype is a focused learning test for selected users, data and situations. Going live requires a separate decision covering security, reliability, privacy, monitoring, access, support, future changes and who is responsible.
What can a focused prototype test?+
A prototype can test whether selected inputs produce useful outputs in realistic situations with agreed human checks. It should expose uncertainty and failure. By itself, it cannot prove that a live system will be reliable, adopted, compliant or commercially successful.
What information should we include in the first brief?+
Describe the operating problem, current steps, users, systems, delays or errors, aggregate volumes, existing attempts, required human approvals, sensitive-data constraints and the decision a useful test should support.
Should we send customer or employee records through the enquiry form?+
No. Use aggregate and non-sensitive context in the generic brief. If a deeper assessment is appropriate, data access, permission, storage, minimisation and deletion responsibilities are agreed before records move.
How does AI workflow automation keep a human in the loop?+
The workflow names which outputs are suggestions, which actions need review, who can override a result, how low confidence is handled and what is prohibited from automatic execution. The same human-in-the-loop discipline applies to AI and conventional business process automation.
How do you measure whether a prototype is useful?+
The plan defines representative scenarios, expected behaviour, quality or operating measures, human review, failure categories and stop conditions before testing. Evidence is recorded against those measures rather than relying on a polished demonstration.
Can Gibson work with our existing systems?+
Existing systems can be assessed, but compatibility is not assumed. Access, supported interfaces, source and destination fields, credentials, rate limits, failure monitoring and ownership are confirmed before an integration is included.
Who owns the code, data and ongoing operation?+
Ownership, accounts, hosting, data, licences, documentation, support and change responsibility are stated in the written scope. This page does not promise one universal handover or deployment model.
What does AI Consulting cost and how long does it take?+
Price and timing depend on workflow breadth, evidence, systems, risk, users, prototype fidelity, evaluation, approvals and production requirements. Gibson confirms the exact assessment, AI prototype or AI implementation boundary in writing before commitment.
07 · CHOOSE THE NEXT STEP
Bring the workflow problem, not a preselected tool.
Tell Gibson what is failing, who owns the process, which systems and evidence exist, what must remain under human control and what decision a useful test should support. Albert or the senior team will confirm the appropriate next step.