Unlock the value of your data, discover powerful insights, and uncover hidden patterns with our Data Science Lab
In the Data Science lab, we work to identify the most important areas where AI solutions will impact your business.
We start with an assessment of your current data flows and select the right use-case for a Proof of Concept.
We will work together with your data analytics and IT team, the management and domain experts. Working closely with your teams, we set up a secure data environment within which to access your large volumes of data—a necessary step in discovering the new patterns and train the models. With the domain expert, we set the priorities for the use-cases. This means your team is always in the loop about how we look at, analyze, and report on your data.
Discovering the Power of AI
The power and potential of AI are evident, but establishing a sustainable data science capability is a challenge for every organization.
In the second step, we work on embedding data science across your enterprise. We engage more stakeholders on all levels, gain trust and support for the needed transformation and help you create a high-functioning, data-driven culture. Simultaneously, we will train the people who are involved with the AI solution: software engineers, domain experts and data analysts.
Improve, Integrate and Align
The Data Science lab will focus on new innovations and techniques, develop new solutions, and improve the models, which are created from data analyses in the first stage.
If the Proof of Concept (PoC) is a success, we broaden the initiative. We do this by integrating the data science capability and aligning it with your business processes. Intellerts’s Data Science lab will focus on new innovations and techniques (see below), build new solutions and improve on current models to be applied across your entire organization. To make this a smooth, efficient and beneficial process, we will also engage more stakeholders throughout your company along the way.
Our Data Science Lab Toolbox
Time-series forecasting is central to an efficient and robust supply chain, yet the practice remains largely confined to short-horizon forecasts. Advances in neural networks are enabling much more powerful capabilities, leading to better forecasting systems.
As an analytics discipline, predictive modelling tries to anticipate scenarios that have never happened before (i.e., is a client likely to buy this service). AI has improved on predictive modelling, and by making use of more data (including text and images), we are able to discover the “unknown unknown”.
Offering shoppers a set of items that they are likely to buy is the key to high conversion rates. Being attuned to a fluctuating set of diverse factors including recent behavior, product properties, unknown shoppers and the daily market are also valuable tools for increasing e-commerce sales.
Advanced sales and marketing analytics optimizes your investments and efforts in sales and marketing.