Solutions

The four business pillars of graph analytics

Our approach for graph analytics is based on fully utilizing relations between different data points through structural connections between data in relational databases, THE data format for most data in corporations. We utilize graph analytics and sparse matrix computations to boost analytics on such data formats.

Predict

Predicting churn, sales, purchasing patterns, as well as market and demographic trends - beyond simple regression.

Typically ML algorithms run on data tables, ignoring complicated relations between different tables (e.g. predicting sales performance on historical sales data, ignoring how the products, channels, buyers, sales teams, etc. change).

Understand

Understanding your business through advanced customer, channel, product and other segmentation and structural analytics.

Customers are typically connected to each other in complicated ways, use different channels, different products, different locations, have different goals,... our models treat this as crucial input for customer understanding, beyond the superficial.

Operate

Organizational data is complex, both in size and connections (different departments, organizational structure, collaboration networks, teams, data produced).

Taking control of such data can improve organizational performance by up to 15% for medium to large size companies.

Build

Dynamic pricing, product recommendations, adaptive content, insights,... graph analytics supports important differentiators for your business applications.

Graph machine learning is already used in most of big tech companies to improve their digital products.

Custom Solutions

We work with industry leaders in different industries, developing custom-made solutions for graph analytics for different use cases, as well as preparing use cases, simulations, implementation plans and conducting specialized trainings.

We offer our software as a stand alone solution, or in combination with consulting projects lead by our retail experts with decades of retail operations experience.