Data you can put to work
Data becomes valuable when information from equipment, ERP, CRM and other sources can be compared and combined. We help organise its collection, storage and processing so analysts, managers and AI services can work with clear, verifiable information.
What the solution includes
- Connecting sources, ingesting data and processing it.
- Data warehouses, data lakes and analytical data marts suited to your needs.
- Quality checks, shared master data and access management.
- Data preparation for reporting, forecasting and model training.
From the first task to launch
We start with your data sources and the questions your business needs to answer. We design the architecture, launch the first data pipeline and check data quality. We then connect more sources, set up monitoring and provide operating procedures.
Questions and answers
Do we need to move all data into one system?
Not necessarily. Storage and exchange methods depend on your goals, source availability and business constraints. The first stage can use a selected dataset while retaining existing accounting systems.
Can we connect data from ERP, 1C and equipment?
This integration can be included after checking available interfaces, formats and access rights. Data mapping rules and exchange frequency are agreed separately.
What is needed to prepare data for AI?
First, define the model’s task and permitted sources. Then check data quality, completeness and usage rights. Depending on the use case, the project may include cleansing, labelling, dataset splitting and update monitoring.
What determines timelines and costs?
Costs depend on the processes involved, data condition, number of integrations and deployment requirements. After assessment, we agree on stages, acceptance criteria and an estimate. Licences and hardware are priced separately.
What do we need to provide to get started?
A description of the task, process participants and existing systems. Data access is agreed separately; anonymised examples can be used in the first stage.