How much does business automation cost in Australia?
There is no useful single price for business automation because two workflows that look similar on the surface can require very different amounts of work underneath.
A simple connection between two well-documented systems is very different from automating a process across five platforms, handling inconsistent data, building custom logic and managing exceptions.
Custom software and automation projects typically start from A$2,500. Final pricing depends on the systems involved, complexity and scope.
Rather than relying on a generic market average, the better way to understand cost is to look at what actually drives the work. If you are new to the topic, our guide to what business process automation is covers the basics first.
The biggest factors that affect automation cost
1. Process complexity
A workflow with three clear steps is easier to automate than a process with multiple branches, approval paths and exceptions.
For example:
Simple workflow: a web form is submitted → create a CRM contact → notify the sales team.
More complex workflow: a request arrives → identify request type → validate information → check customer status → route to the correct team → create records across several systems → trigger an approval if certain conditions are met → send the appropriate response → monitor for exceptions.
Both are "automation", but they are not the same project. We cover where one ends and the other begins in workflow automation vs business process automation.
2. Number of systems involved
Every additional platform adds another set of questions.
- Does it have an API?
- Does it support webhooks?
- What authentication method does it use?
- Are there usage limits?
- Which system should be the source of truth?
- What happens if one platform is unavailable?
Connecting two modern cloud tools with strong APIs may be straightforward. Connecting a legacy system, spreadsheet and custom database can require much more work.
3. API and integration availability
The easiest integrations usually involve systems that already provide reliable APIs or native integrations.
When they do not, alternatives may include scheduled imports and exports, middleware, database access or custom workarounds. Our article on what to do when your business software doesn't integrate walks through those options in more detail.
The more indirect the connection, the more care is required around reliability, monitoring and failure handling.
4. Data quality
Automation works best when the information entering the process is consistent.
If customer names are stored differently across systems, required fields are missing or teams use spreadsheets in inconsistent ways, part of the project may involve cleaning up the underlying data flow before automation is safe.
Automating poor data simply moves poor data faster.
5. Exception handling
The normal path is usually the easy part.
The real work often sits in questions such as:
- What if required information is missing?
- What if a customer already exists?
- What if the API fails?
- What if the value is above an approval threshold?
- What if two systems disagree?
- What if the job needs human judgement?
Reliable automation needs a clear answer for the situations that do not follow the normal path.
6. Custom interface or software requirements
Some automation can run almost entirely behind the scenes.
Other projects need a custom form, internal dashboard, approval screen or customer portal. Once a project includes a user interface and custom application logic, the scope starts moving toward custom software rather than a simple integration. If that is where you are heading, see how much custom software costs in Australia.
7. AI requirements
Traditional automation works well when the rules are predictable.
AI becomes useful when a process involves reading documents, interpreting emails, extracting information or classifying unstructured data.
That can add requirements around model selection, prompting, testing, confidence thresholds, human review and privacy.
AI should be used because the process needs it, not because adding AI makes the project sound more advanced.
Three common project categories
Simple integration or focused automation
This is usually a narrow workflow between a small number of systems.
Examples include:
- sending website enquiries into a CRM
- creating tasks after a deal reaches a certain stage
- syncing a defined set of customer fields
- sending internal notifications based on system events
The process is clear, the systems are accessible and there are relatively few exceptions.
Multi-step business process automation
This involves several stages, systems or teams.
Examples include:
- customer onboarding across CRM, accounting and delivery tools
- quote generation, approvals and follow-ups
- document intake and processing
- job status updates across operations and customer communications
These projects usually require more discovery because the automation needs to reflect how the business actually works, not just connect two applications. The CorIT Tech onboarding project is a real example of this kind of work: customer details held in the CRM now create the project and its tasks without being retyped.
Custom software or AI-heavy automation
At this level, the business may need custom logic, an internal interface, a portal, a bespoke data layer or AI processing.
The project is no longer simply "connect tool A to tool B". It may involve designing and building a system around the process itself.
This is where proper scoping matters most, and it is why larger projects start with an initial consultation rather than a quick quote.
A simple way to think about automation pricing
A useful cost model is:
Project cost = discovery and process mapping + implementation + integrations + testing and deployment + any ongoing support
The exact balance changes by project.
A small workflow may need very little discovery and mostly implementation. A complex operational process may need significant mapping before development starts because automating the wrong process is more expensive than spending time understanding it first.
What ongoing costs should you expect?
Some automation projects have little ongoing cost beyond the software subscriptions already being used.
Others may include:
- automation platform subscriptions
- API usage
- hosting
- AI model usage
- monitoring
- maintenance
- changes when third-party systems update
- ongoing support or improvements
These costs should be identified during scoping rather than appearing after launch as a surprise. Where a workflow becomes important to daily operations, ongoing support can cover monitoring and changes over time.
The hidden cost of choosing the cheapest build
A low initial quote is not automatically a bad sign. A simple problem may genuinely have a simple solution.
The risk appears when important work is left out of scope.
Common examples include:
- no error handling
- no monitoring
- no documentation
- duplicate records created when a workflow runs twice
- credentials stored poorly
- no plan for API limits
- no testing of unusual cases
- workflows only one person understands
An automation that works perfectly in a demo but silently fails in production can create more work than the manual process it replaced.
What information is needed for a proper estimate?
You do not need a technical specification before speaking to a provider.
A useful starting point is:
- What process are you trying to improve?
- What triggers it?
- Which systems are involved?
- What information moves between them?
- Which steps are repetitive?
- Which steps require judgement or approval?
- How often does the process happen?
- What goes wrong today?
- What would a successful outcome look like?
That information is usually enough to determine whether the project is a small integration, a broader automation or something that requires custom software.
When automation is not worth the cost
Automation is probably not the right investment when the process happens rarely, changes constantly or has little operational impact.
It may also be better to use an existing feature in your current software, simplify the process or replace a poor-fit tool rather than building around it. We cover that decision in should you automate a process or replace the software?
The aim should be a sensible return on the work, not automating everything possible.
Frequently asked questions
How much do 23Labs automation projects start from?
Custom software and automation projects typically start from A$2,500. Final pricing depends on the systems involved, complexity and scope. Larger or multi-system projects are scoped through an initial consultation.
Can you give a fixed price before discovery?
For a clearly defined small workflow, sometimes. More complex projects normally need enough discovery to understand the process and exceptions before a reliable fixed scope can be produced.
Is custom software always more expensive than automation?
Not necessarily, but custom software usually involves more design, development and testing because the interface and application logic also need to be built. The right comparison is whether improving existing tools solves the problem before replacing them.
Do automation projects require ongoing support?
Not all of them, but support can be useful when a workflow depends on third-party APIs, business rules change regularly or the automation is important to daily operations.
Get the process scoped before choosing the technology
If you want a realistic estimate, start with the workflow rather than a list of tools.
23Labs can review the current process, identify what should and should not be automated, and scope the simplest approach that solves the actual problem, whether that is business process automation, system integrations or something smaller. If you have a process in mind, tell us how it works today and we can talk it through, with no obligation.