Customer Acquisition & Retention
Have clarity on your customers' purchase journeys.
Targeted Communications
Target your communications more efficiently and control commercial risk.
Recommender Systems
Analyze customer preferences and predict which products they are more likely to interact with next.
Churn Prediction
Predict which and when customers will leave your brand and adjust expected revenue.
Customer Segmentation
Create segmentations that are meaningful for the business and optimize the marketing spend.
Sales Forecasting
Increase accuracy in your forecasts, and supply better business planning, detailed metrics, and analysis.
Cross Selling Algorithms
Predict future actions, plan offers, and increase purchases.
Trial Period Analysis
Take a deeper and quicker analysis of your trial period data.
Deep Analytics & Insights
Predict the factors that count in lead conversion and drive your sales.
Whether you want to build a Proof-of-Concept (POC) or solve a large organizational pain point using data, we can improve your decision-making using Machine Learning or Data Science.
Product Forecasting
We’ve done multiple forecast models for our diverse base of retail customers. Our models aren’t only tied to past sales data but incorporate contextual information relevant to explain the demand of each product.
Computer Vision
Extract insights from your photos or videos. Be able to identify and track new insights or automate manual processes.
No Data works without Data Engineering. As Data Scientists and Data Engineers, we understand how to manage and organize data to fit your business needs.
Cost Optimization
Optimize your cloud infrastructure to reduce your costs.
Computer Vision
Build data pipelines and aggregate data from different sources. Combine data with external datasets for new KPIs.
MLOps are a crucial part of any Data & AI development. Because most companies stay in the POC stage, we are experts in setting up state-of-art MLOps best practices and helping you leaving the never-ending POC loop.
Model Monitoring and Retraining
Investigate your model drift and retrain it based on triggers.
Pipeline Testing
Make sure that your deployed model receives exactly the same type of data structure that you used on the development phase.