Every day your business generates gigabytes of information: CRM transactions, website clicks, ad channel visits, warehouse stock. But for most companies, this data lies dead in disparate Excel spreadsheets. You make key decisions based on intuition, losing margins on excess stock or missing out on customers due to unnoticed churn.
AI Analytics from STARCODE is a transition from stating past facts to forecasting future events. We develop and implement machine learning (Machine Learning) mathematical models that analyze your historical data series, find hidden relationships, forecast demand taking seasonality and promo activities into account, automatically segment clients by LTV, and signal anomalies in real time.
Maximum accuracy of sales forecasts of our ML models after calibration
AI finds anomalies and generates reports faster compared to manual analyst work
Warehouse inventory surplus reduction through accurate supply planning
Automatic anomaly monitoring (Telegram alerts for sudden metric changes)
Our goal is not just to paint pretty colorful charts. We create a tool for making management decisions. You will know exactly which product will bring profit next month and which client is on the verge of leaving for a competitor.
We build end-to-end systems that turn the chaos of scattered spreadsheets into clear business insights.
Most reports only show history: what happened last month. We train machine learning algorithms on your historical data to look into the future. Scripts forecast sales down to specific product categories.
Before launch, we always perform backtesting — checking model forecast accuracy against historical periods.
Segmenting customers manually by gender and age is inefficient. AI groups the audience by behavioral patterns: purchase frequency, average order value, lifetime value (LTV), churn probability, and discount sensitivity.
This allows your marketing department to make targeted offers that pay off significantly better than standard email blasts.
For analytics to work stably, we build a centralized data warehouse (Data Warehouse). We write ETL pipelines (data collection scripts) that automatically collect and clean information from CRM, 1C, Metrika, and SQL databases.
All data is stored in a single place in an optimized format, speeding up the generation of any reports by 100 times.
Sequential process of designing and training models to achieve guaranteed data accuracy.
We research which systems you use (CRM, 1C, ERP, SQL databases, trackers). We evaluate the quality of accumulated information, table structures, and identify "dirty" data.
We develop a database architecture (DWH) on ClickHouse. We write Python scripts for automated collection, cleaning, filtering, and merging of data from all sources.
We select mathematical algorithms for the task (XGBoost, Prophet, neural networks). We train models on historical company data, tune weights, and account for external factors.
We create clear interactive dashboards in Google Looker Studio or Power BI. We set up key business metrics (CAC, LTV, ROI, ROMI, Churn) filtered by date ranges.
We compare model forecasts with real historical results. We calibrate parameters to achieve maximum data convergence and minimize errors.
We deploy the system into production. We configure Telegram/Slack bots to automatically send daily summaries to management and instant anomaly notifications.
We use modern machine learning, database, and visualization tools.
The main development language for analytical scripts. Pandas is used for fast table cleaning, Scikit-Learn for customer classification and segmentation, Facebook Prophet for time series forecasting.
ClickHouse from Yandex is an ultra-fast columnar database optimized for processing billions of rows of analytical logs. PostgreSQL serves as a reliable storage for business structures.
Professional BI systems for building intuitive, interactive reports with filtering by dates, managers, products, and ad campaigns.
The price depends on the number of databases being merged and the complexity of mathematical forecasting models.
| Features | Basic dashboard To visualize key business metrics 75 000 ₽ Timeframe: from 10 days Order | Popular Predictive analytics Database Integration and ML Forecasting 140 000 ₽ Timeframe: from 20 days Order | Turnkey DWH End-to-end analytics for large companies from 250 000 ₽ Timeframe: from 35 days Discuss |
|---|---|---|---|
| Integrable Data Sources | up to 3 sources (GA4, Metrica, CRM) | up to 6 sources (1C, SQL databases, ads) | All company databases without limits |
| Building a data warehouse (DWH) | Local analytical database | clickHouse / BigQuery storage | |
| Sales and demand forecasting models | 1 predictive ML model | Set of models for different departments | |
| Customer base segmentation | RFM clustering by LTV | Real-time behavioral segmentation | |
| Anomaly tracking and alerts | Weekly email reports | Telegram alert bot (Real-time) | |
| Guarantee of data consistency and TOR compliance | 14 days | 30 days | 90 days |
| Training for analysts and marketers | Dashboard Manual | 1 educational webinar | Full course + 1 month support |
Still have questions on how to make your data drive profit? Submit a request — our lead analyst will conduct an express evaluation of your databases.
Submit a request and describe what data sources you have. Our lead data architect will analyze your database structure and propose the optimal solution for building predictive analytics.
Order AI analytics