01
Operational platforms
One view of sensor readings, robots and work.
Bring status, history and actions into a usable workspace for operators.
What we provide.
We connect data sources, build usable tools and apply machine learning where it helps interpret images or signals.
Software that connects the work.
Platforms, analytics and machine learning should make existing operations clearer and more useful.
02
Predictive analytics
Find patterns that may point to emerging issues.
Assess whether historical and live data support useful forecasts or maintenance signals.
03
Image recognition
Flag visual features or changes for review.
Train and validate models against images from the actual environment, with human oversight.
04
Alerts & workflows
Turn events into assigned actions.
Route a signal to the right person and record what was checked or changed.
05
System integration
Connect existing equipment and software.
Design reliable data exchange across devices, platforms and operational tools.
06
Reporting & insights
Summarise trends, exceptions and outcomes.
Present practical information that helps teams decide what to do next.
Connect information to daily work.
Jakrok works on operational software and data connections around the tools your team uses. That may involve a shared dashboard, alerts linked to assigned work, or an application that brings sensor and equipment information together. Applied machine learning can help interpret images or patterns where suitable data exists. The useful decision and the people making it come first.
Existing systems and data
Identify the records, equipment signals, software interfaces and access permissions involved. Map how information is captured, checked and used today.
A usable workflow
Define what operators need to see and do. Connect status, alerts and actions so the software supports a real process with clear ownership and a record of what happened.
Evidence and validation
For predictive analytics or computer vision, assess data coverage, quality and representativeness. Agree how accuracy, uncertainty and human review will be evaluated before deployment.
Questions about software and machine learning.
- What is the difference between image recognition, computer vision and machine vision?
- Computer vision describes methods for interpreting images or video. Image recognition is one application, such as identifying a feature of interest. Machine vision usually describes the complete practical system, including cameras, lighting, processing and integration. The terms overlap; the important question is what needs to be observed and how the result will be used.
- What could a computer vision application look like for a grower?
- An illustrative workflow is capturing images of a crop or asset, flagging a visual feature for review, and linking the observation to an assigned check. Consistent capture conditions, representative examples and a defined decision are needed. A possible application is not a guarantee of disease detection, yield prediction or reliable performance in every field condition.
- Can you connect our existing platforms and equipment?
- We assess the interfaces, data formats, permissions and operating requirements of the systems involved. The aim may be to bring readings into a shared view, pass an event to another platform or connect an alert with an action. The scope identifies what can be integrated, the reliability needed and who supports each part.
- Do we need machine learning for our project?
- Not every useful software improvement needs a model. A dependable data connection, a clear dashboard or a well-defined alert may meet the need. Where machine learning is relevant, feasibility work checks whether the available images or historical data can support the intended task and how results will be validated.
Illustrative workflow
A practical path from signal to action.
01
Collect
Bring camera, sensor and work records together.
02
Interpret
A model flags a point of interest for review.
03
Act
A team member accepts, assigns or closes the task.
LET’S EXPLORE YOUR OPERATION.
Tell us the task or information gap you want to work through.