AI boutique agency for Australian companies
Over 15 years building systems companies trust.
What our customers say
Client review“Fab has been instrumental in modernising and automating our reporting.”
Mandy ProwseResearch & Insights Manager, Art Gallery of NSW
Client review“Working with Fab Solutions transformed how we approach data across our organisation.”
Client review“We can now access actionable insights on a daily basis without labouring through manual processes and legacy tools.”
Trusted clients
What changed, in numbers
Only real figures.
back on reporting at the Art Gallery of NSW, with automated reporting across multiple data sources.
Art Gallery of NSWof performance across the organisation at Sydney Metro, tracked against the metrics that matter.
Sydney Metroat Velocity Frequent Flyer: insights every day, without the manual processes and legacy tools.
Velocity Frequent Flyerbuilding the reporting Macquarie's operational and executive teams depend on, in their Associate Director's words.
Macquariemore likely to qualify a lead when a business replies within the hour instead of an hour later.
of employees' time today goes on activities that current AI could take on.
Client review“Fab has been instrumental in modernising and automating our reporting.”
Mandy ProwseResearch & Insights Manager, Art Gallery of NSWClient review“I would recommend any organisation to look into data management and analytics with Fabricio. An investment that will pay dividends.”
Sarah TanData Centre Site Acquisition & Development, APAC, ESR / AETEDRecommendation“Any organisation looking for a high-performing data and analytics professional would be fortunate to have him on their team.”
Client review“Fab has been instrumental in modernising and automating our reporting.”
Mandy ProwseResearch & Insights Manager, Art Gallery of NSWClient review“I would recommend any organisation to look into data management and analytics with Fabricio. An investment that will pay dividends.”
Sarah TanData Centre Site Acquisition & Development, APAC, ESR / AETEDRecommendation“Any organisation looking for a high-performing data and analytics professional would be fortunate to have him on their team.”
Client review“Working with Fab Solutions transformed how we approach data across our organisation.”
Client review“We can now access actionable insights on a daily basis without labouring through manual processes and legacy tools.”
Client review“Working with Fab Solutions transformed how we approach data across our organisation.”
Client review“We can now access actionable insights on a daily basis without labouring through manual processes and legacy tools.”
What we do
Nearly every audit lands on the same four gaps. Build closes them one piece at a time and leaves you a foundation. Care makes sure none of it quietly goes stale.
Your prices, clients and the way you work live in inboxes, spreadsheets and people's heads. The AI gets none of it, so every chat begins blank.
We give your AI a memory of your business.
Someone writes a great prompt, it gets copied and changed, and soon there are four versions that do not match. Meanwhile enquiries wait and follow-ups get forgotten.
One library of skills, and agents that use it to do the work.
Scripts on someone's laptop die quietly. Nobody knows what ran last night, or whether it did.
FDX OS. Every agent in one place.
Models get swapped, staff come and go, the way you work drifts. Left alone, AI slowly goes stale.
We stay on it, month in, month out.
Who does the work
Each option begins with the audit. Most businesses hand the building to us.
The audit shows where the hours go. We build each piece into the apps your team already opens, test it with you, then look after it every month.
A good fit if: no one in the team has spare hours for this and you want it done properly.
Memory, the AI team and the cockpit come from us. Your people learn to write skills and run agents on top of them, with short sessions after each build and us on call.
A good fit if: someone in the team already uses AI every day and wants to go further.
Sitting with your people, they sort out the data your agents rely on, build the agents on top, and show your team how it all works as they go.
A good fit if: you have a larger team and lots of systems, and want it done from the inside.
“He is someone who can be trusted to work independently on complex initiatives while also collaborating effectively across teams and business functions.”
Use cases
One example per industry: how the work runs today, what we would build, and what changes. Your team approves every message, price and decision before it goes out.
A partner asks, “Which portfolio companies supply the defence sector?” An analyst searches investment papers, shared folders, meeting notes and the CRM.
A shared company brain that searches approved information, prepares an answer and links each finding to its source. Each person only sees information they have permission to access. An analyst checks the answer before it goes to an investor.
The team spends less time finding information and more time assessing what it means. The same knowledge supports investor updates and quarterly review preparation.
A recruiter selects candidates, then spends hours emailing availability, chasing replies, arranging interviews and updating the candidate tracker.
The recruiter selects the candidates and approves the invitation. An assistant coordinates available times, prepares calendar bookings, drafts reminders and updates the tracker. The recruiter approves outgoing messages and sees exceptions that need attention.
One place shows who is booked, who has replied and who needs a follow-up. More of the recruiter’s day goes into candidate conversations and client relationships.
A studio owner exports attendance, membership and payment data, builds a spreadsheet and checks which trial visitors never returned.
A weekly report showing attendance, trial conversions, renewals and outstanding payments. An assistant highlights changes and prepares follow-up messages for the owner to approve.
The owner starts the week knowing what needs attention, with the supporting figures and next actions ready.
After a site visit, a builder has photos, measurements and voice notes scattered across their phone. Preparing the quote becomes an evening job.
The builder uploads the site notes. An assistant organises the scope, uses the business’s approved rates and templates, flags missing details and prepares a draft quote. The builder checks quantities, pricing and exclusions before sending.
Site information becomes a consistent quote with less retyping. The builder can see which enquiries still need details, a quote or a follow-up.
A restaurant receives function enquiries by email and social media. Staff repeatedly ask for dates, guest numbers, menus and dietary requirements.
An assistant gathers the event details, checks the venue’s booking calendar and prepares a package using approved menus and prices. The manager reviews the proposal and confirms availability before it goes out.
Each enquiry reaches the manager with the information needed to make a decision. Customers receive clearer proposals, and fewer enquiries disappear between shifts.
A consultant finishes a client call, rewrites the notes, searches for an old proposal and manually creates the follow-up tasks.
Using approved meeting notes and proposal templates, an assistant drafts the scope, deliverables, open questions and next steps. The consultant approves the fees and commitments before sending. Once accepted, the agreed work becomes an onboarding checklist.
Less time rebuilding documents after every meeting. The proposal and delivery team start from the same agreed information.
A tenant reports a problem by email. The property manager chases photos, contacts trades, seeks owner approval and manually writes progress updates.
An assistant organises the request, asks for missing details through approved messages and prepares the owner approval request and trade brief. The property manager reviews urgency, approves spending and controls the instructions sent.
Every maintenance job has a clear status and next action. Tenants and owners receive consistent updates, with less information copied between messages.
Staff answer the same questions about vehicles, dates, prices and pickup arrangements, then copy customer details between booking records and emails.
An assistant gathers trip requirements, checks current fleet availability and prepares a quote for staff approval. After confirmation, it prepares the booking record, pickup instructions and pre-trip checklist for review.
Staff spend less time repeating booking admin and more time helping customers with unusual requirements or changes to their trip.
A lawyer reads through emails, discovery documents and file notes to build a dated chronology by hand before advising the client.
An assistant reads the matter documents, sorts each event by date with its source and drafts a short summary. Access stays per matter. The lawyer checks every entry before it is used or sent.
Less time assembling the file and more time on the advice. Each entry links back to the document it came from.
Site supervisors send photos and notes in different places, and someone in the office rewrites them into an update for each client.
The supervisor sends the notes and photos. An assistant turns them into a clear update for each client, stage by stage, and flags selections still missing. The supervisor checks each update before it goes out.
Clients know where their build is without calling. The office spends less time rewriting site notes.
After each client meeting, an adviser writes the file note from memory and chases the statements still missing from the fact find.
An assistant prepares a one page brief before the meeting, drafts the file note and the actions after it, and requests missing documents with approved messages. The adviser checks everything. FDX never gives financial advice.
File notes are done the same day, and advisers spend more of their week with clients.
Everything we set up runs in your own accounts and on your own systems. Nothing is kept on our side, all of it belongs to you, and private details are masked before any AI reads them.
Free preview
Add your website and work email. In under a minute you get a short preview of where your hours go, what to fix first and what we would connect. Free, and it is yours to keep.
No drawn-out proof of concept. Three steps, each priced before it starts.
“Fab has been instrumental in modernising and automating our reporting.”
$2,000 flat 7 to 21 days
We talk with up to 10 of your people, and every conversation comes back to one question: which part of your week should a machine be doing? You get a ranked list of what to build, with the hours and dollars on every line.
Go ahead with the build within 30 days of your report and the full $2,000 comes off it.
$2.5k to $35k per build About two weeks per build
Memory and the AI team go in first, then the work on top. Each build is quoted on a call as a range and goes live inside the apps your team already opens.
~$900/month Every month after
We look after what we built: fixes, small changes as your business moves, and a monthly look at what is being used and what to build next.
People are frank with someone from outside about where their day really goes. The audit looks for jobs a machine ought to be doing, never a person to replace.
Getting AI to work is not a box you buy, it is someone in your corner. This is who you get.
Founder
Yes. Everything we set up runs in your own accounts and systems, nothing is kept on our side, private details are masked before any AI reads them, and your data is never used to train AI.
No. Everything we set up is yours and lives in your own accounts, so it stays with you whatever happens.
No. We begin with what you have and fix what matters along the way.
The audit is $2,000 flat, and it comes off the build if you go ahead within 30 days. A build is $2.5k to $35k, quoted before anything starts. Care is about $900 a month after that.
Some of it, yes, and we can train them to do it on top of the foundation we lay. What usually falls over is the upkeep. That is what Care is for.
Reading files is a start. It still does not know how your business runs: who does what, which jobs repeat, what a good reply looks like. We build that memory, and the agents that use it, inside the apps you already open.
Bring them in early. Everything runs in your own accounts and systems, so they can see every piece we set up.
No. They are there to sort out the data your agents rely on, build the agents and show your team how it all works. Day to day IT stays with whoever looks after it now.
The audit looks for jobs a machine ought to be doing, never a person to replace. The point is to give hours back for the work only people can do.
Automations reply on their own in your voice. Emails wait as drafts for your yes. Everything is logged in one place.
That is what Care is for. We look after what we built every month, fix what breaks and adjust it as your business changes.
Our own product: an AI team on one screen that answers, follows up and remembers. See FDX OS.
AI Time Audit
Tell us a little about your business and what eats your week. We reply in person, usually the same day.
