Our Approach
Data Collection
Using past events to analyze the data for patterns and build predictive models using machine learning algorithms to see trends and predict future events
Get Valuable insights
Understanding the data clearly to get insights. Visualizing the data to improve model performance and identify potential issues that could impact its accuracy
Train models
Training our machine learning models to iteratively adjust the parameters of the model to minimize the cost function and to provide approximate solutions that solve problems easily
Deploy
Deploy the model on a server or integrate it into a software system using a web service or API, as well performing ongoing model maintenance and retraining ML models on further updates.
Area of Expertise
CNN Services
Providing your business with an automated way to process and interpret images to identify objects, recognize facial expressions, determine the sentiment, and discover other features.
Regression Analysis Services
Providing insights into how your enterprise operates by analyzing the data that affects your business, improving your decision-making and future predictions
Use cases
A complete suite of ML models to outperform the competition in accuracy
Sales and Marketing
- Automated lead scoring
- Next most advantageous offer prediction
- Price history tracking
- Customer segmentation
- Churn prediction
- Lifetime value prediction
- Propensity to buy the prediction
- Direct marketing response prediction
Healthcare
- Automated detection of potentially harmful drugs in medical prescriptions
- Prediction of patient no-show rates for appointments
- Estimation of length of stay for in-patients
- Detection of fraudulent insurance claims
- Prognosis of disease progression in individual patients
- Prediction of readmission rates for in-patients
- Assessment of risk factors for developing certain diseases
- Development of personalized treatment plans for individual patients
Banking
- Automated fraud detection in financial transactions
- Detection of money laundering
- Credit risk analysis
- Automated chatbots for customer support
- Intelligent document processing for loan applications
- Spot fraudsters creating multiple accounts
- Detects hacking
- Spot and stops fake reviews
Customer Service
- Automated customer service through chatbots or intelligent FAQ systems
- Sentiment and behavioral analysis to improve customer satisfaction and retention
- Customer segmentation based on behavior or characteristics
- Predictive analytics for identifying customers at risk of cancellation
- Personalized product recommendations to increase customer interest and satisfaction
Manufacturing
- Inspecting products on an assembly line for defects
- Analyzing sensor data to predict when equipment will need maintenance
- Forecasting demand for inventory and optimizing stock levels
- Scheduling production based on forecasted demand
- Planning production and delivery to minimize costs and maximize efficiency
- Training the data from past quality assurance tests to ensure that the product meets quality standards.
Technology
- Predictive models to recognize patterns in data and make forecasts about future events
- Classification models that allocate labels to data points relying on specific aspects /li>
- Regression models that can envision continuous values such as prices or probabilities
- Clustering models that can group data points based on resemblance
- Recommendation approaches that propose items or services to customers based on their past behavior