The ring-in for CTOs who got handed the AI brief
Synap AI is a Fractional AI Advisor for Australian mid-market businesses. Senior AI judgement and hands-on execution on a monthly retainer, so you make the right calls without hiring a full-time Chief AI Officer you cannot yet justify.
Book a discovery conversation
A straight conversation about what you are trying to figure out. No pitch.
No commitment, no pitch. A senior conversation about what you are trying to figure out.
Most AI strategy lands on the wrong desk
Leadership says do something about AI. It gets handed to whoever already runs the technology, the CTO, the COO, the one IT manager, on top of everything they already own. None of that is an AI specialism, and it shows: disconnected experiments, licences nobody opens, pilots that never move an operational number.
The fix is not another tool. It is senior judgement on what to build, what to defer, and what to not build at all, from someone who does this full time.
AI is a specialism, not an infrastructure problem
Most mid-market AI work fails because it is handed to whoever runs the tech, without specialist judgement on what should and should not be built.
Restraint matters as much as ambition
Working out which projects to not do is often worth more than building the next thing.
Capability transfer is deliberate
Engagements are built so your team learns alongside the work, not after it. You are not left dependent on us.
Operational outcomes are the only metric
Licences distributed and pilots completed are not evidence of value. Movement on the numbers leadership cares about is.
How the work runs
Every engagement runs on a three-phase rhythm, with four problem areas worked in parallel. The phases run in sequence; the time split flexes with the complexity of what we are addressing.
Discover
Observe and Orient
Gather the data. Map the current state across the relevant problem areas. Find the highest-impact opportunities, and the gap between what is actually happening on the ground and what leadership thinks is happening.
Design
Decide
Turn findings into prioritised work pathways. Decide what to build, what to defer, and what to not do. Specify the architecture, the governance, and the capability transfer plan for each piece.
Implementation
Act
Build, test, deploy, measure. Move the operational metrics. Iterate as evidence comes in, and transfer capability to your team as the work progresses.
Underneath each cycle is an OODA loop, borrowed from military strategy because it is built for situations that keep changing while you work in them. AI deployment is one of those.
| Observe | Gather data and resources from the live environment |
|---|---|
| Orient | Make sense of the patterns and the underlying problems |
| Decide | Choose a specific work pathway |
| Act | Implement, measure, and feed the result into the next observation |
Four problem areas, worked in parallel
Most operational problems do not sit cleanly inside one function. Pretending they do produces incomplete solutions.
Marketing and Sales
Lead generation, customer engagement, content production, sales process automation, customer insight.
Operations
Workflow automation, process optimisation, document handling, reporting, exception management, capacity planning.
Finance
Invoicing, reconciliation, financial reporting automation, forecasting, compliance documentation, audit support.
HR
Recruitment workflows, onboarding, capability development, psychosocial risk monitoring, internal communications.
Engagement options
Three durations, scaled to the depth of work needed. Duration is committed at signing.
3 months
Scoped pilot
A focused engagement in one priority problem area. One full Discover, Design, Implementation cycle.
Best for: validating whether AI can move a specific operational metric before committing to broader transformation.
6 months
Pilot plus expansion
Begins with a scoped pilot in one area, then expands into a second adjacent area. Two Discover, Design, Implementation cycles.
Best for: proving the approach in one area before broadening, while keeping commercial momentum across the year.
12 months
Full operational transformation
Four Discover, Design, Implementation cycles across all four problem areas.
Best for: making AI a core capability across the business, with the internal capability transfer to maintain it afterwards.
Pricing
Priced on two dimensions: the size of your organisation, and the intensity of the engagement. All figures are monthly retainer fees, plus GST.
| Intensity | Hours / month | On-site | Also included |
|---|---|---|---|
| Light | 8 | None | Remote advisory and oversight |
| Standard | 16 | 1 day / month | Plus 1 online leadership meeting / month |
| Intensive | 24 | 2 days / month | Plus 1 online meeting, plus priority support for urgent requests |
| Organisation size | Light | Standard | Intensive |
|---|---|---|---|
| Tier 1 0–25 staff | $1,200 | $2,500 | $3,500 |
| Tier 2 25–100 staff | $4,200 | $6,500 | $8,500 |
| Tier 3 100+ staff | $7,200 | $12,500 | $15,500 |
Per month, plus GST. The retainer covers strategic oversight, build oversight, and the nominated hours. Larger builds outside that scope are quoted separately as fixed-scope projects. On-site sessions within metropolitan Melbourne are included; travel beyond that is billed at cost. For most mid-market organisations, Standard at the right size is the sensible starting point.
Case study: Dragonfly
Engineering reports, from 330 hours to a first draft
Dragonfly's core deliverable is the report. Each one took an engineer roughly 330 hours: reviewing field defect imagery by hand, identifying remediation requirements, writing findings, and producing a client-ready document. For a business whose product is the report itself, that was the bottleneck.
Synap built a workflow that ingests the defect imagery, uses multimodal AI to identify defect type and remediation pathway, and drafts the structured recommendations a senior engineer would normally write by hand. Every AI output passes through a named human approver before it becomes part of the official report.
- Senior engineers back on judgement work, not documentation
- Faster turnaround on client engagements
- More capacity without more headcount
- A full audit trail across every suggestion, edit, and approval
Other engagements
Cybermate
Fractional Chief AI Officer providing strategic oversight on the AI roadmap, governance, and vendor evaluation for a cybersecurity business operating in regulated environments.
Full Support
Fractional CAIO supporting a multi-phase business automation platform across NDIS government work-file management, covering all six platform phases from architecture to production.
Phusion
AI chat wrapper and email campaign automation for a multi-business pharmacy and retail portfolio, providing operational uplift across the associated businesses.
Who you work with
Hamish Mackellar, Founder and Fractional AI Advisor
Twenty years across software development, network engineering, and cloud architecture. Prior advisory work with Bupa and Chemist Warehouse. Currently holds fractional Chief AI Officer engagements with Cybermate and Full Support, alongside project work in sectors with data sensitivity and audit requirements comparable to financial services.
Synap AI Pty Ltd · ABN 86 695 003 653 · Level 8, 805/220 Collins Street, Melbourne VIC 3000
Common questions
A consultant hands you a deck. An agency builds what you ask for. A Fractional AI Advisor sits closer to a senior hire: shared judgement on what to build and what to avoid, hands on the execution, and capability left behind with your team. It is a monthly retainer, not a one-off project.
No. Part of the job is transferring capability to the people you already have. Where a build needs specialist hands, Synap does it, with your team learning alongside the work rather than after it.
Strategic oversight, build oversight, and the nominated hours each month (8, 16, or 24 depending on intensity). Larger builds outside that scope are quoted separately as fixed-scope projects.
Movement on the operational metrics leadership already cares about. Licences distributed and pilots completed are not evidence of value. Outcomes are.
Synap AI is Australian owned and operated, data stays on Australian servers, and we work in sectors with data sensitivity and audit requirements comparable to financial services.
Three, six, or twelve months, committed at signing. Six months is the most common: prove the approach in one area, then expand into a second.
Not sure where AI actually fits? That is the conversation.
Bring the brief you were handed. We will talk through where AI moves a number for you, and, just as usefully, where it does not.
Book a discovery conversationPrefer to talk?
Call or email directly. Happy to have a no-obligation conversation about where AI fits in your business.