Less manual work
Business process automation
We automate stable, repetitive tasks where there is a clear process owner, data source and way of handling exceptions. The goal is simpler work, not another layer of tools. We work with companies across Poland and the EU.
On this page
Who this service is for
- companies copying the same data between systems
- teams preparing recurring documents and reports by hand
- organisations connecting ecommerce, inventory, CRM or ERP
- companies where mistakes in re-typed data cost time and complaints
When it is not the right choice
- automating a process that has no agreed rules
- replacing high-risk decisions without human review
Concrete scope
What the project can include
process map and points of failure
priorities based on time, risk and value
integration or workflow with event logging
error handling, retries and a manual fallback path
documentation and measurement of the operational effect
Clear process
From problem to working solution
- 1
Observation
We describe how the work really runs: systems, data and exceptions.
- 2
Control design
We agree rules, permissions, logs and the moments that need a person.
- 3
Small first scope
We launch one workflow with clear value and a safe way to roll back.
- 4
Measure and grow
We check errors and time saved before extending the automation.
Which processes to automate first
The best candidate is a task done often, by fixed rules, on data that already exists in a system. Such a process can be described, tested and measured.
If the same step looks different for every person on the team, we first agree the rules. Automating a chaotic process only produces mistakes faster.
- the task repeats daily or weekly
- the rules can be written down without “it depends” exceptions
- the input data lives in a system, not only in someone’s head
- a mistake or delay has a real cost for you or your customer
Automation examples for a small business
These workflows show a typical scope. Each one requires checking the APIs, permissions and data quality in your own systems.
- an online store order reaches the ERP and stock levels update without re-typing
- a website enquiry creates a CRM contact and notifies the right person
- documents are generated from approved data instead of hand-filled templates
- a daily sales and low-stock report arrives automatically
- payment and deadline reminders are sent according to agreed rules
- orders from delivery platforms arrive in one view for a restaurant team
Integration before artificial intelligence
In many companies the biggest effect comes from reliable data synchronisation, rules and notifications, not from an AI model. We add AI where it helps classify or draft something and where the result can be checked.
Every critical workflow needs logging, an alert and a manual procedure. Automation without visibility only moves the problem elsewhere.
Odoo, API integrations or a separate tool?
When sales, inventory and documents are scattered across many programs, a shared system such as Odoo ERP is worth considering. When you already use proven tools, connecting them through APIs is usually enough.
We choose the approach after an audit: the number of systems, their interfaces, data volume and who will maintain the workflow after launch.
- Odoo ERP — one system for sales, inventory, purchasing and documents
- API integrations — connecting existing systems without replacing them
- queue-based workflows with an event log — when error control and retries matter
How we check whether automation pays off
Before building, we estimate the time spent on a task, how often it happens and the cost of mistakes, and compare that with the cost of building and maintaining the workflow. If the numbers do not add up, we say so openly.
After launch we measure handled events, errors and manual interventions, and decide on that basis whether to extend the automation.
Data security
Workflows get only the permissions they need. Access keys are stored outside the code, and every operation on data leaves a trace in the logs.
If the automation processes personal data, we agree roles, data scope and the legal basis for processing under the GDPR before launch.
Timeline and terms
A simple workflow can be launched in stages. Integrations with several providers require an audit of APIs, data quality and error scenarios.
FAQ
Common questions before we start
Where should automation start?
With a frequent task that has clear rules and a measurable cost of manual work. We stabilise the process first, then automate it.
How much does process automation cost?
It depends on the number of systems, the quality of their APIs and the number of error scenarios. We start with a short audit of one process and a quote for the first workflow.
How long does an automation project take?
A single workflow between two systems can usually be launched in stages within a few weeks. Larger projects are split into stages with separate sign-off.
Does automation have to use AI?
No. Rules, queues, APIs and good data are usually the foundation. AI is an option only for the right kind of task.
Do I have to replace my current systems?
Not always. If your systems offer APIs, they can be connected. We consider replacing them only when integration would be more expensive or less reliable than a shared system.
What happens when something fails?
The workflow should have a log, an alert, a way to retry and a manual path. Specific service levels are agreed in the scope.
Next step
Show us a repetitive task in your company.
Describe the systems, data and manual steps. We will check whether to start with one workflow and where human review is needed. Sending an enquiry does not create a paid contract.
Ask for a consultation