Automation, data and IoT
We automate repetitive tasks, organize data and connect equipment. We integrate tools where needed and define how to handle errors and exceptions.
Start with the idea or problem. You do not need a technical solution already designed.
Trackable workflows and data, with alerts and people responsible for exceptions.
When this service makes sense
- Documents that need field extraction and checking
- Reports that disagree about sales or inventory
- Equipment whose condition needs monitoring
What we deliver
- Map of the workflow, data and required connections
- A working flow or dashboard, according to scope
- Alerts, failure handling and monitoring criteria
Compare approaches before defining the project
- Alternatives
- Compare native system features, API or file integration, rules and sensor monitoring. Define the event requiring action and the person responsible first.
- Initial scope
- One task or signal, an alert rule and an owner. Include repetition, missing signals and human verification in the acceptance criteria.
- What affects time and cost
- Available interfaces, data quality and frequency, connectivity, equipment and field installation. Software, sensor procurement and installation are separate responsibilities and scope items.
- Delivery and continuity
- The proposal defines acceptance criteria, documentation, responsibilities and access to the commissioned deliverables. Support, hosting, third-party services and future development have explicit scope and terms; they are not assumed to be included.
How we develop the project
The work advances in short stages, with documented decisions and review before expanding scope.
- step 1Task automation and data exchange between systems
- step 2Metrics with clear sources and calculation rules
- step 3Sensors and equipment connected to operations
When this is not the right path
Not every operation needs sensors or AI. The solution must fit the team’s routine, with review for sensitive decisions.
Questions to define scope
Short answers to understand when this path deserves to become a project.
Does automation and IoT require new infrastructure?
Not always. First we read what already exists: sensors, systems, databases, spreadsheets, queues and rules. New infrastructure enters only when it solves a real constraint.
How does operational data become reliable decision support?
With identified source, minimum quality, exception rules, monitoring, owner and review. Data must explain what changed and what should happen next.
What if the automation breaks a critical process?
Every workflow ships with a fallback and a manual path: if a rule fails, the process returns to a person, not to limbo. A critical decision never runs without a defined stop point.