T-DAB INDUSTRY SOLUTIONS
Our case studies. Real examples, real results.
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.
Increase customer engagement through personalised experiences and recommendation engines and maximise revenues by improving demand forecasts and optimising supply chains.
Improve operations by automating repetitive tasks and engaging chatbots as virtual assistants for consumer interaction and sales agents, and predict market trends to secure the competitive advantage.
Enhance patient care and diagnosis, whilst reducing costs and improving response times through automation and improved medical imaging. Increase insight by collecting device IoT data and rapidly summarising research for discovery.
Improve decision making and increase profitability by better understanding your customers and market trends to recommend services and solutions, and reducing risk and anomalous behaviour.
Optimise asset performance through improved outage management and energy distribution, predicting asset anomalies to increase resolution time and better understand customer needs and pain points.
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.
check out
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.
T-DAB initially used one years worth of data to use machine learning to firstly mine the dataset for key influential features from an initial list of 64, and then apply machine learning to predict spoilage and tool failure events within future time periods. Included were machine state, output quality, tool life and operational data.
T-DAB first carried out a data audit, cleaning, and wrangling exercise, followed by feature engineering. Machine learning experimentation was carried out in R.
The end result was that a number of ML algorithms were produced able to predict spoilage and tool failure events to a degree of accuracy significant enough (>80%) to have real world impacts on operational processes in reducing spoilage and downtime.
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.
T-DAB developed an automated data mining process and leveraged machine learning algorithms in open source R to help the client better understand where to focus their resources and develop a strategy to target specific consumer groups and market sectors. This involved both automated machine learning processes and inferential statistical modelling methods
The team then built on this and used R-Studio to build an analytical tool, driven by machine learning and statistical models, to allow users to interactively explore consumer relationships and test market scenarios.
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.
T-DAB designed a solution incorporating machine learning driven AI into the machine calibration. This would enable the manufacturing machines to dynamically adjust and optimise their function while still in operation, saving development time and cost.
A holistic approach incorporating Azure cloud distributed and localised computing services, edge deployment, IoT, and cutting edge deep learning frameworks (Deeplearning4j) was proposed. This allows for the machines to be calibrated as part of the learning process (i.e. training algorithms on data of inputs and outputs during operation), and in turn will allow the machines to dynamically adapt and optimise their function while still in operation.
Productisation of Publicly Available Insurance Solvency II Data for B2B Marketing.
T-DAB scoped, trialled and built a new visualisation product by helping the client quickly scope and assess their data product requirements and build a clear development roadmap.
The team provided an end to end service providing expertise to guide them through the selection of the appropriate technology for delivery of the product, first building a proof of concept, followed by a minimum viable product, and a first go-to-market. The solution was delivered using a combination of on premise My SQL database and Tableau visualisation software
Cloud architecture and machine learning to enable predictive analytics for a super-material manufacturer.
T-DAB designed and built a suitable AWS architecture to batch ingest and database test data from individual .csv files
This consisted of an automated process for file upload to Amazon S3. A scheduled Amazon ECS C# process pulled bucket and data inserted to MS SQL database. For security, this was contained in a private subnet. An amazon EC2 R server instance in a public subnet was connected to MS SQL DB. IAM role and security group restricted access to ECS and EC2 only. An elastic load balancer in a public subnet above the EC2 R Server instance subnet and IP access was restricted using Security Groups. The R server instance was connected to provide an analytics layer. This was used for training ML regression-like algorithms to predict super-material performance.
Project mobilisation and advisory for super materials manufacturer.
T-DAB have been working alongside the strategic projects directorate and technical team leads for the last 6 months.
T-DAB have delivered a range of services. This has included; strategic consultancy on the value and feasibility of data projects, scoping and planning of data projects, liaison with key technology providers, solution architecture design, advisory on technology choices, and recruitment advisory.
T-DAB have also provided data auditing services, data exploration, as well as PoC work to help inform project planning and long term decision making.
changing your
future together
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.
MARCH & APRIL ’23 ROUND-UP!
Hello May! As we welcome the new month, we are looking back at the busy and exciting months of March and April. We were so busy in fact, we’ve rolled two months’ worth of roundup material into one. We are nothing but efficient, right? Sit back, relax, grab a coffee, and let’s catch you up on everything we’ve been up to the past 2 months…
T-DAB.AI win Innovate UK Grant for OctaiPipe
T-DAB.AI has secured an Innovate UK grant for their OctaiPipe project, which aims to develop a secure and privacy-preserving machine learning platform for IoT and edge devices. The project will focus on four main axes to address vulnerabilities in machine learning for IoT and promote the rapid adoption of OctaiPipe at scale.
FEBRUARY ’23 ROUND-UP 🥞
After a long cold January, we soon saw the shortest month of the year, February! Whilst brief, it was still busy and action-packed here at T-DAB.AI. Here’s what we got upto…
Edge AI Explained: How OctaiPipe Is Revolutionising IoT
Read our blog post to discover Edge AI technology up close, and learn how OctaiPipe unlocks its full potential with federated machine learning.
JANUARY ’23 ROUND UP: LOOKING BACK & MOVING FORWARD 🚀
And just like that, it’s a new year and January is done and dusted! An exciting time for many businesses with the fresh prospect of new opportunities and growth.
Benefits of Federated Learning Explained
Federated learning is here to unlock greater privacy and accuracy in machine learning. Read our blog to explore its benefits, differences, and functions.
Summer Round up 2022
Welcome to the latest instalment of our blog series, a monthly newsletter where we look back at the highlights of the month and share what’s coming up next!
Leading Edge Hardware Manufacturer Partners with UK Edge AI platform
World-renowned AIOT solution-ready provider, EverFocus, has agreed on a partnership with T-DAB.AI to integrate their Edge AI platform into their device portfolio.
State-of-the-art Edge AI platform to accelerate UK’s AI adoption
UK deep tech AI company, T-DAB.AI, has closed their funding round of £495,000 to accelerate the development of their Edge AI platform.
Supply Chain Analytics for Business Pt.2
In the second part of the supply chain analytics for business, we discuss on how tech is transforming the supply chain whilst dealing with demand volatility with predictive and prescriptive analytics
and what the future holds.
Exploring Supply Chain Analytics for Business
Now, more than ever, a business’s ability to react to the rapid shifts in the market is dependent on its supply chain and having visibility and insight across the entire ecosystem.
Discover how supply chain analytics can help businesses anticipate shifts in demand, proactively manage their resources, improve efficiencies and address potential risks throughout their supply chain ecosystem.
AI inside & outside the factory
Manufacturers are resetting priorities around resilience, sustainability and operational excellence. AI & Machine Learning powered technologies are playing a vital part in accelerating capabilities and capture market share.
Industrialising Machine Learning II
In the 16th episode of the business intelligence report in partnership with Bright Talk, we’ll be taking a deeper look into machine learning solutions, in particular, data-centric machine learning and machine learning pipelines, in conversation with Rajdeep Biswas, Director, Advanced Analytics & Machine Learning at Microsoft and Nik Spirin, Co-founder & CEO at Metapixel AI
Industrialising Machine Learning
In the 16th episode of the business intelligence report in partnership with Bright Talk, we’ll be taking a deeper look into machine learning solutions, in particular, data-centric machine learning and machine learning pipelines, in conversation with Rajdeep Biswas, Director, Advanced Analytics & Machine Learning at Microsoft and Nik Spirin, Co-founder & CEO at Metapixel AI
Artificial Intelligence: Trends & Focus
Take a look at the trends that we have seen this year as a base to look at new advancements in 2022
Introduction to ML Ops
Introduction to ML Ops: How to start integrating ML solutions in your strategy
Introduction to Machine Learning Pipelines
In this blog, we will discuss what pipelines are and why they are a fundamental unit against which the value of your ML investment should be measured.
Built to scale: Ramping up AI projects
Take a look at the key points that emerged from the 2021 AI & Big Data Expo panel – Built to scale: Ramping up AI projects.
How to start your Data & Analytics Strategies
Chief Data Officers recognise the importance of data in making sound business choices, but often struggle to link data to specific business advantages and outcomes.
The Importance of data in manufacturing
Data is at the heart of manufacturing. However, with the advent of digital technologies and AI and ML the collection and use of data has taken on new importance. See how manufacturing is reshaping thanks to data and new technologies
How to deliver digital transformation in manufacturing
Delivering digital transformation relies on knowing the art of the possible and how to integrate these new technologies within your organisation and your people.
Press Release T-DAB & Situ Live
T-DAB.AI and Situ Live team up to deliver the ultimate retail experience through AI & ML
Predicting UTI Risk In Care Homes Pt. 2
This article marks the conclusion of the project, its findings and new potential areas of development. Read the transcript from the episode with Eric Topham (ERIC), Kohdai Komorya (K), Hamid Khandahari (H) and Emily Naylor (E).
Why Data Has Gravity
Cognition as a Service (CaaS) with a distributed learning framework for performance, cost efficiency and data privacy
Artificial Intelligence: Edge vs Cloud Pt.3
what are the factors influencing the future of AI for manufacturers and which synergies must be implemented?
Artificial Intelligence: Edge vs Cloud Pt.2
What is the edge and cloud paradigm for manufacturers and what is the role of AI and Machine learning?
AI To Combat “Fake News”
Fake news. We’ve probably fallen victim to it once or twice, and it does a perfect job of illustrating how everyday technology platforms like Facebook can come with a few unintended consequences. We caught up with Inpulsus, a born-digital consulting firm that helps companies transform their marketing to try and answer the question: Can AI combat misinformation on social media?
Artificial Intelligence: Edge vs Cloud
How are manufacturers making the best choice between edge and cloud? Read more in the first article of the series.
AI applications in the retail industry
Technological innovation and the increasing capabilities of AI are continuously developing to make the retail experience as efficient as possible. How is Machine Learning (ML) and Artificial Intelligence (AI) making waves in retail?
Scaling AI: From Proof of Concept (POC) to Production
How machine learning can overcome getting trapped in the Proof of Concept loop and help you scaling your solutions
AI & Machine Learning in the Healthcare industry
Take a look at 3 applications of AI and Machine Learning that are disrupting the healthcare industry
Supply Chains for 2021
Supply chains are incredibly complex, and vulnerable to inconsistencies and inefficiencies. There is great potential for supply chain components to be revolutionised by automated AI
Machine Learning Procedure at T-DAB.AI
In a previous article, I described the 4 development standards we developed at The Data Analysis Bureau (T-DAB) for the successful delivery of machine learning projects. It featured a table that listed the components that
Data & AI trends for 2021
This article captures our latest view on the data & AI trends in 2021 and the advent of wider adoption
Artificial Intelligence in Space Exploration
What may have seemed like a distant endeavour years ago, artificial intelligence in space exploration is now a reality. Latest space launches from Space X and NASA and the
Predicting UTI Risk in Care Homes
Listen to the episode HERE 2021 marks the second year of The Innovation Sandbox and will see us embark on several new projects, as well as some existing projects, with new students, new clients and new partnerships. The
ML and NLP for E-Commerce
Listen to the episode HERE 2021 marks the second year of The Innovation Sandbox and will see us embark on several new projects, as well as some existing projects, with new students, new clients and new partnerships. The
The 2021 Innovation Sandbox
2021 marks the second year of The Innovation Sandbox and will see us embark on several new projects, as well as some existing projects, with new students, new clients and new partnerships. The Innovation Sandbox is a collaborative initiative at the
Machine Learning Development Standards at T-DAB.AI
As the data science and machine learning specialists, we are known for building data solutions that include machine learning (ML). We help clients and partners
Microsoft Awards Gold Data Analytics Status to T-DAB.AI
We are incredibly pleased to announce that we have obtained a Gold Data Analytics Partner accreditation with Microsoft. This Data and Artificial Intelligence focused competency
How to prepare for AI in 2021?
Over the last few years (and virtually in 2020), we have hosted several Data & AI Readiness workshops with our clients and partners to better
Time-Series of Information Technology Operating Analytics Part 4
In Time Series for Information Technology Operating Analytics part 4 blog, as the last blog of the Series, I will showcase in detail the anomaly
Multivariate Time Series Clustering
This Multivariate Time Series Clustering project follows the development of a Long Short-Term Memory (LSTM), as part of T-DAB’s Innovation Sandbox, to predict the rudder movements that a sailor would make during a race. If you’re familiar with The
How Is AI Enabling Chatbots For Good?
A combination of the sophistication of Artificial Intelligence (AI) technology and a desire to simplify the interaction between humans and computers has led to the
Time-Series of Information Technology Operating Analytics Part 3
In Part 3 of the Time-Series of Information Technology Operating Analytics article series, I have included the literature used and the current trial experiments. Firstly,
AI & Machine Learning in Finance & Portfolio Management
What is the impact of AI & Machine Learning In Finance & Portfolio Management and how are they helping decision-makers have the best tools and
Text Summarisation Part 2
In this Text Summarisation Part 2 article, I wanted to follow up on my recently published Part 1 on automatic text summarization, the field of
3 Ways AI & ML Can Change How You Interact with Our Workforce
Being in the aftermath of a global pandemic, the effects of the virus were felt by almost every worker in the UK. Millions of workers
Building Manufacturing Resilience Through Industry 4.0
Building Manufacturing Resilience Through Industry 4.0 is an essential activity for any manufacturer that wants to keep competitive. In this article, I will look at
Time-series of Information Technology Operating Analytics – Part 2
In the Time-series of Information Technology Operating Analytics – Part 2 we will explore anomaly detection and the role this had on my research and
Mental Wellbeing at Work
Mental wellbeing at work and workplace health have always been important for businesses, but it is only recently that these aspects are being really considered
Time-series of Information Technology Operating Analytics
With the time-series of information technology operating analytics blog series, I wanted to introduce you to time-series and its use in information technology operating analytics. This
Data science in the capital markets
Join T-DAB.AI and CJC Ltd as we explore the impact of data science in the capital markets and volatility of Covid-19 and benefits of data science and
Bringing forth a digital twin
When the elite of the world’s sports sailors let their boats sail off in the Vendée Globe sailing race later this year, the boats will
Algorithm breakdown for Teaching AI to Sail
Algorithm Breakdown: Teaching AI to Sail Hopefully you are familiar with our Innovation Sandbox program, where students from one of the UK’s top university join
Text Summarization from the Innovation Sandbox
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.
Innovation & AI: Our Story so Far
Our Story So Far: T-DAB Innovation Sandbox Years before starting T-DAB.AI, our founder and Head of Data Science, Eric Topham, was already sailing for pleasure
T-DAB Lab: Innovation Sandbox
In the fast-moving multidisciplinary field of commercial data science and engineering, staying abreast and ahead of rapid technological change is key. T-DAB’s mission is to
The Importance of Collaboration in Technology
An ecological perspective on collaboration for developing intelligent solutions Unlike the scientific advances of the late 19th and early 20th centuries, the technological developments of the 21st are
Supervised learning vs unsupervised learning
Machine Learning is all about understanding data, and what can be taught under this assumption. This post introduces supervised learning vs unsupervised learning differences by taking the data side, which is often disregarded in favor of modelling considerations.
Setting up an Experimentation Data Science Environment in Azure
It can be daunting to navigate different tools and answering a simple question, “where to start?”. If you have some data on your hands and you want to do some data science and you want to do it NOW, this post will explain how to “switch on” the infrastructure you need.
How can AI manage the Stress and Mental Wellbeing effects of Covid-19
Explore the opportunities in cognitive technologies and meet SAM, the mental health chatbot to support stress and mental wellbeing effects.
What is the opportunity cost of Machine Learning
Machine Learning & Artificial Intelligence are the technologies of the future. But what is the opportunity cost associated with their application?
Top 5 uses of machine learning in manufacturing
What are the top 5 manufacturing issues solved by Machine Learning (ML)? Here are some examples of the most common problems and how they are solved by ML
The ML & AI Opportunity in 2020
Do you want to find out more? Get in touch with the team or sign up to your blog for the latest insights and exclusive
3 Ways Brands Use Big Data & Machine Learning
This is only one example of where brands use big data & machine learning to bring huge business benefits. What could you do? Download The
3 Observations from the Smart Factory Expo
Do you want to find out more? Get in touch with the team or sign up to your blog for the latest insights and exclusive
Top 3 challenges for manufacturers when going digital
Rapid changes are taking place as we enter the era of Industry 4.0 and Smart Factories. So what are the top 3 challenges for manufacturers
Insights from IOT Solutions World Congress
How does Machine Learning play a part in the IoT solutions ecosystem? Explore our insights from the event & take inspiration from partner solutions and their journeys to the IoT Solutions World Congress 2019.
Join us at the IoT Solutions World Congress
Do you want to find out more? Get in touch with the team or sign up to your blog for the latest insights and exclusive
We’re supporting the Wirehive 100s: digital agency awards
Do you want to find out more? Get in touch with the team or sign up to your blog for the latest insights and exclusive
T-DAB bring Apogee Software into the fold
Do you want to find out more? Get in touch with the team or sign up to your blog for the latest insights and exclusive
T-DAB and CJC partner to help clients maximise the predictive power of IT Operations Analytics
Do you want to find out more? Get in touch with the team or sign up to your blog for the latest insights and exclusive
3 Vitals Steps for Manufacturers to Return Value from Data Solutions
How capable is your team in turning business problems into data solutions? Digitation is not rocket science: start with the problem then develop a solution.
Agfa Graphics: A Data Driven Transformation Case Study
How capable is your team in turning business problems into data solutions? We think the answer is that it is so obvious! Agfa started with