Explore Data & AI in action
Our case studies. Real examples, real results.
Explore Data & AI in action
Our Case STudies.
Real examples, Real results.
We deliver Value
In many industries.
T-DAB.AI data scientists can use data to obtain value for your company in any number of different ways. The possibilities are almost endless and our data scientists can help you explore these. You may already have a lot of data available already and some you may need to collect.
Embrace Industry 4.0 and drive intelligent solutions through the adoption of machine learning and predictive analytics to increase production and quality, reduce costs and waste, and manage production remotely.
The challenges presented by our clients range from simply increasing supply chain visibility with interactive dashboards to optimising machine performance through machine learning driven AI. We’ve delivered a range of exciting projects for our customers utilising our data accelerator framework.
It provides the support to identify a unique data roadmap, clearly communicating available services to select and build solutions, and manage on-going operations.
our DATA IN ACTION.
Prediction of spoilage and failure events in the manufacturing chain for a leading packaging manufacturer.
A global manufacturing company was looking to bring predictive analytics to its packaging production line.
In particular, they were keen to understand how machine learning could be applied to reduce machine downtime and spoilage from production errors.
Statistical Modelling and ML Driven Data Mining of Variables Predicting Consumer Behaviour.
A FMCG company needed to improve their consumer modelling and analytics to drive their retail and marketing strategy.
The marketing teams needed to run multiple scenarios to understand how changing consumer perceptions and targeting certain demographic groups may allow them to alter the market share of different products.
Application of Machine Learning Driven AI to a Cutting Edge Manufacturing Company.
A UK manufacturer needed to optimise their composite material production to reduce operational downtime and development cost.
In addition, the client works with experimental masses of material, often operating beyond the current understanding of how these composite materials behave.
This meant the client needed to regularly change, test and review the production setup, often slowing production, increasing costs and risking delivery.
Whatever the case, T-DAB.AI works closely with you to define your challenge, even before you begin collecting data. We give clients the ability to identify the value of their data, obtain the best return and mitigate risk, and deliver insights that drive better decisions.
Over the last few years, considerable progress has been made in the field of Automatic Text Summarization- the branch of Natural Language Processing concerned with building programs which can automatically summarize written content. This article, the first of a mini-series on this area, gives a short outline of the field and an overview of some of the leading approaches.