Make AI
prove it.
AI isn’t the goal. A better business is.
AI might help you increase sales, improve margins, serve customers faster, create more capacity or simply give your people time back.
It has to prove which one.
Show us what’s slowing you down
Your business doesn’t need an AI problem. It has business problems.
- The quote that takes half a day.
- The spreadsheet somebody rebuilds every Friday.
- The same customer question answered again and again.
- The information buried across emails and folders.
- The process everyone knows is painful but nobody has fixed.
That’s where we start.
We help you work out what actually needs to change first, and whether AI needs to be part of the answer at all.
What should get better?
- More sales
- Better margins
- Faster service
- More capacity
- Fewer mistakes
- Better customer experience
That’s what we measure.
AI is simply one way we might get you there.
Your people know where the value is.
The people doing the work know where customers get frustrated, where sales opportunities disappear, where time gets wasted and which processes look simple on paper but aren’t. That’s why we involve them early.
We use AI to remove repetitive work, increase capacity and help people make better use of what they know. Not remove the judgement your business depends on.
A clever idea is still just an idea until it improves something that matters.
Before AI gets the job, it has six questions to answer.
Problem
Is there a real problem worth solving?
Alternatives
Is AI actually the best answer?
Value
What will improve if this works?
People + ownership
Will people use it, and who is responsible for checking it?
Risk
What happens when it’s wrong?
Evidence
Can we prove the result before spending more?
Pass? Scale it.Fail? Stop.
Sometimes AI loses.
And we’re completely fine with that.
- Maybe the process needs fixing first.
- Maybe software you already own can solve it.
- Maybe simple automation is cheaper.
- Maybe your people need better training.
- Maybe AI works technically but does not improve the business enough to justify the cost or disruption.
The point isn’t to use AI.
The point is to improve the business.
What can we actually help you with?
You don’t need to know which AI tool you need. You don’t even need to know where to start. Tell us what you’re trying to improve and we’ll work from there.
Find what’s worth fixing.
AI opportunity & adoption
Work out where AI could actually make a difference.
We work with your team to find opportunities across sales, operations, customer service, finance, marketing and everyday admin. Then we help you decide what is worth doing first.
Automation & workflow improvement
Not every problem needs AI.
Sometimes the better answer is automation, integration or simply fixing a broken process. We help work that out too.
Prove it.
AI pilots & proof of value
Test it before you bet on it.
We take a real business problem and test whether AI can improve it. Small first, measurable result, then a decision about whether to scale.
Put it to work.
AI tools & implementation
Turn the useful ideas into something people can actually use.
We help select, configure and implement the right tools and workflows. Where possible, we start with technology the business already owns rather than adding another platform.
Sales & customer experience
Use AI where it can help you grow, not just save time.
Find opportunities, prepare proposals, improve follow-up, make customer information easier to find, respond faster and remove repetitive work from sales and service teams.
Help people use it.
AI training & adoption
Teach your people how to use AI for the work they actually do.
Practical training built around the work people actually do. Axcel helps teams understand where AI can help, how to use it well, how to check its output and how to adopt it without removing the human judgement the business relies on.
Keep it safe.
AI safety & governance
Use AI without losing control of it.
We help put practical rules around AI use, data, privacy, human review, responsibility, approved tools and what happens when something goes wrong.
Keep improving it.
Ongoing AI support
AI doesn’t finish when the tool goes live.
We can continue working with the business as people adopt it, new opportunities appear, tools change and new risks emerge.
So how do we actually do this?
We start inside your business.
Look at the business
We talk to the people doing the work and look at where sales are being missed, customers are waiting, admin is piling up, information is getting stuck or people are repeating the same work.
Find what’s worth changing
We identify the opportunities that could make a meaningful difference and compare AI with simpler options.
Test it on real work
We use real work, real data and a small pilot to see what actually changes.
Put it to work and keep improving it
If it earns its place we help implement it, train the people using it and put sensible controls around it. Then we keep looking for the next thing worth doing.
Small first. Evidence next. Scale last.
Before we recommend scaling anything, we agree on what success should look like.
Hours saved, sales created, turnaround time reduced, rework reduced, customer response time improved, capacity gained.
If we can’t measure what changed, we haven’t proved very much.
We come at AI from different directions.
Eleanor brings technology, AI adoption, safety and commercial experience. Vlado brings research, product design, manufacturing and commercialisation.
Together, Eleanor and Vlado look beyond the technology to understand the people, processes, customers and commercial realities around it.
Because most AI problems aren’t really just AI problems.
Eleanor Harris
AI Adoption, Safety & Commercial Strategy
Eleanor Harris has spent more than 25 years working in technology and enterprise sales, including seven years at Cisco and working at IBM, working with organisations across complex technology environments.
Eleanor now focuses on a question that matters more than simply giving a business another AI tool: where can AI genuinely improve the business, and where can it create new problems?
Eleanor works across practical AI adoption, training and safety, helping organisations identify where AI can create measurable value while protecting the human judgement the business relies on.
Eleanor is also the founder of Headlights, an independent research project documenting real-world AI incidents and identifying the governance patterns behind them.
Vlado Baban
AI, Product Development & Commercialisation
Vlado Baban works across the journey from identifying an opportunity to turning it into something that can be built, used and scaled.
Vlado’s experience spans market research, product development, design thinking, prototyping, manufacturing, software selection, technology deployment and commercial growth. Vlado works with organisations to understand requirements, design practical solutions and take new products and services from concept through testing and implementation.
At Axcel, Vlado applies that experience to AI as well. That means looking beyond the AI model itself to the workflow, user requirements, data, systems, integration and commercial case around it.
When an AI opportunity proves worthwhile, Vlado can help shape what needs to be built and work with development capability to move it from prototype into a usable business solution.
We study what happens when AI gets it wrong too.
Alongside our commercial work, we research real-world AI incidents. That means we see the predictable ways AI projects go wrong: misplaced trust, poor checking, weak controls, confusing ownership and technology used where it never really fitted the work.
We bring those lessons into the way we test AI, train people and put controls around it before small problems become expensive ones.
Headlights · What did the AI agent actually do?From proof to something you can use.
Finding the opportunity is only the start.
When an idea proves itself, we can bring in the right development team to build it out, integrate it with your existing systems and turn a successful pilot into something your business can actually use.
That might mean an internal AI tool, workflow automation, customer-facing application, integration or a more complete product.
We don’t start by building technology. We build when the evidence says it’s worth building.
Find itTest itBuild itPut it to workImprove it
You don’t need an AI department.
Built for Australian businesses with roughly 10 to 100 people. You just need to know:
Where can AI genuinely help?
What’s worth doing first?
What will it cost?
Will our people actually use it?
What could go wrong?
Is it worth it?
That’s what we help you answer.