Automation AI / data analytics for business
Data analytics
We convert data from platforms, files and applications into indicators that the team can track.
Background
When this service makes sense
Reports, data models and dashboards for decisions based on actual information.
- Main needdata analytics for business
- Role in the projectAI agents, document processing and automation connected to real processes, with rules, logbooks and human verification.
- Result pursuedWe convert data from platforms, files and applications into indicators that the team can track.
Deliverables
What usually comes into the project
The exact list shall be adjusted after the audit, but these modules frequently appear in data analytics projects.
01Data Audit
02Model KPI
03Source Connection
04Dashboard
05Exports and reports
Connection
Service works better when it's connected to the rest of the project
Any service works better when connected to the rest of the ecosystem: content, SEO, data, operation, hosting and maintenance.
- AI agents
- Document processing
- Sales automation
- Integration with AI platforms
Recommended pages
Pages related to this type of service: technologies, fields of activity, guides and complementary services.
Frequently Asked Questions
Before we begin the project
Choice, stages and support for Data Analytics.
01 / Choice
What's useful to know
Data analytics require perfect data?
Not perfect, but consistent enough. We start by seeing what data is and what needs to be cleaned up.
What information are we preparing for the first discussion?
Examples of requests or documents, process steps and approved sources. We clarify what data can be used, who validates the result and what actions require approval.
02 / Planning
Purpose, budget and stages
What can the project include?
For Data Analytics, starting points are: Audit data; KPI model; Source connect; Dashboard; Exports and reports. In the offer we specify deliverables, limits and responsibilities; the list adapts to your situation.
How do we set the budget and the timetable?
We separate data preparation and integration from the cost of use. The volume, models, external services and the level of human verification influence the estimation; we start with a limited and measurable flow.
03 / Continuity
Verification and support
How do you verify the result before handover?
We use representative examples, including difficult cases, and compare results with validated answers or rules. We track errors, costs and required interventions: a fluent response is not proof of accuracy.
What happens after handover?
Updates of sources, adjustments of rules and reassessments of results may be required after launch. We set cost monitoring, usage limits and escalation to a person for sensitive situations.