Development of Products Based on Data Science and Machine Learning
- Identifying factors influencing product quality
- Forecasting equipment failures
- Reduction of defect rates
- Scheduling for equipment maintenance and debugging
- Production optimization for maximum product output
- Forecasting the volume of bond purchases and sales
- Early warning of possible bankruptcy
- Determining the amount of compensation or credit
- Assessing financial solvency
- Detection and prevention of fraud and data leaks
- Managing pricing strategies
- Identification of key value items (KVI)
- Inventory management
- Analysis of customer loyalty levels
- Demand forecasting for products and services
- Streamlining customer registration
- Diagnosing based on disease symptoms
- Identifying disease triggers
- Determining susceptibility to illness
- Providing recommendations and prescribing treatments
- Predicting customer behavior
- Determining the effectiveness of advertising campaigns and channels
- Estimating product demand
- Predicting and preventing customer churn
- Creating personalized offers based on customer interests
- Route optimization and reducing the number of vehicles
- Early warning of potential risks to prevent supply chain disruptions
- Forecasting warehouse occupancy
- Calculating transportation costs with multiple variables
- Predicting transportation efficiency
Complete Data Science development cycle
More than 30 specialists: Data analysts, Data engineers, Data scientists, DBA administrators, ML engineers. We work with various hardware, including RFID scanners, 3D scanners, photo and video cameras, medical devices, and others.
For example, forecasting potential downtime at a facility, road congestion, potential demand for a product, and more.
For example, facial recognition, creating recommendation systems for users (movies, music), inventory control, procurement planning, and more.
Collaboration Options
Individual specialists or a ready-made team under your management on a full-time basis.
- Data Analyst
- Data Engineer
- Data Scientist
- Database Administrator
- Machine Learning Engineer
Full-cycle product development — management, development, testing, and implementation.
Transfer of exclusive rights to the developed software after project completion.
Why it's beneficial to work with us
The solution helps select an apartment, taking into account where family members work and study. The system analyzes travel time and traffic jams, as well as travel time on public transport. Additionally, we displayed nearby infrastructure on the map: stores, ATMs, parking lots, schools, and services.
The system helps a real estate company retain clients and close deals faster. We automated the system of collecting information about houses — the data automatically goes into the CRM, so the realtor spends time on clients, not on paperwork.
The system predicts the prices of apartments and when they will be sold. The algorithm analyzes the average apartment price on the market and shows it to the user. The user can choose the recommended or any other price, and the system will recalculate the time of sale. The higher the price, the more time the deal will take.
We integrated the system into a real estate portal. As a result, the churn of the portal users decreased. The prediction error of the system is within 4%.
We developed a parser of data from 20+ electronic trading platforms. Data is collected on a schedule from web pages, the ability to interact with sites via API (SOAP, REST) is automatically checked. The parser is launched and controlled via HTTP requests.
Project features:
- High requirements for the completeness and quality of the collected data.
- Validation of the site structure for layout changes before data collection begins.
- Parsing data on demand, in real time using a configured filter to all sites.
The solution helps select an apartment, taking into account where family members work and study. The system analyzes travel time and traffic jams, as well as travel time on public transport. Additionally, we displayed nearby infrastructure on the map: stores, ATMs, parking lots, schools, and services.
The system helps a real estate company retain clients and close deals faster. We automated the system of collecting information about houses — the data automatically goes into the CRM, so the realtor spends time on clients, not on paperwork.
The system predicts the prices of apartments and when they will be sold. The algorithm analyzes the average apartment price on the market and shows it to the user. The user can choose the recommended or any other price, and the system will recalculate the time of sale. The higher the price, the more time the deal will take.
We integrated the system into a real estate portal. As a result, the churn of the portal users decreased. The prediction error of the system is within 4%.
We developed a parser of data from 20+ electronic trading platforms. Data is collected on a schedule from web pages, the ability to interact with sites via API (SOAP, REST) is automatically checked. The parser is launched and controlled via HTTP requests.
Project features:
- High requirements for the completeness and quality of the collected data.
- Validation of the site structure for layout changes before data collection begins.
- Parsing data on demand, in real time using a configured filter to all sites.