Data Analytics & BI with AI
AI analyses business data, builds forecasting models, and generates automated reports. Integrates with Google Sheets, Looker, Power BI. Price: €2,000–15,000.
What is AI data analytics for business?
AI data analytics automatically collects data from multiple sources (CRM, ERP, Google Analytics, financial systems), processes it, and delivers clear insights and forecasts to decision-makers.
Unlike traditional BI, AI enables natural language queries — "What were our top 10 customers last year?" — and the system answers instantly with data, without needing SQL knowledge.
What problems does AI analytics solve?
Automated weekly reports
AI collects data from multiple sources every week and sends executives a clear summary with visualisations — no manual work.
Sales forecasting
Machine learning models analyse historical data and forecast sales volumes for the next month or quarter.
Customer behaviour analysis
AI identifies customer segments, purchase patterns, and churn risk — enabling more targeted marketing decisions.
Financial KPI monitoring
Real-time dashboards with automatic alerts when metrics deviate from normal — CFOs see the situation without report requests.
Inventory optimisation
AI analyses sales history and seasonality, recommends optimal stock levels, and warns about impending shortages.
Interactive BI dashboards
Power BI or Looker Studio dashboards with filtering capabilities that every manager can use without technical knowledge.
Indicative pricing
| Project | Price | Timeline |
|---|---|---|
| Automated reports + dashboard | €2,000–5,000 | 2–4 wks |
| Forecasting models (sales, inventory) | €5,000–10,000 | 4–8 wks |
| Full BI infrastructure with AI | €10,000–15,000 | 8–16 wks |
| Monthly maintenance & updates | €300–800/mo | Ongoing |
Frequently asked questions
How much does AI data analytics cost?+
Automated reports + dashboard — €2,000–5,000. Forecasting models — €5,000–10,000. Full BI infrastructure — €10,000–15,000. Maintenance — €300–800/month.
Which tools does it integrate with?+
Google Sheets/Looker Studio, Power BI, Tableau, Metabase, Grafana. Data sources: any SQL database, REST API, Google Analytics, CRM/ERP exports.
How much historical data is needed?+
A minimum of 6–12 months of historical data is recommended for forecasting models. For reports and dashboards, less data is sufficient.
Can managers use dashboards without IT help?+
Yes — that is the primary goal. Power BI and Looker Studio dashboards are built so that a manager can filter, change time periods, and export data independently.
Get data insights automatically
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