Case Studies
Dive into our curated selection of case studies for business transformation. From leveraging academic expertise to delivering powerful data-driven solutions, discover real-world examples of how we’ve empowered companies to make informed decisions and drive success through actionable insights. For more information on our story, see our about us page, alternatively, if you would like to see what we can do to help your business then please contact us.
Empowering Business Interactions: Crafting an AI Chatbot for Enhanced User Engagement and Query Resolution
In response to a client’s need for an AI chatbot capable of addressing various business data inquiries, our team meticulously crafted a solution using the Rasa NLU tool in Python. Designed to understand and respond effectively to a vast array of user queries, from quality and incident data to health and safety concerns, the chatbot underwent rigorous testing and refinements. Though still awaiting deployment due to funding, the chatbot demonstrates significant potential to revolutionize the client’s user interactions while also providing our team with invaluable insights for future endeavours.
Revolutionizing Remote Filmmaking: Seamless Background Removal via Android App
Aiming to revolutionize remote filmmaking, our client sought an Android app that facilitates real-time collaboration between actors across different locations. A standout feature of this app was its capacity for impeccable background removal, allowing actors to engage within a shared customizable backdrop. Our main hurdle was the development of this background removal algorithm. Confronted by the lack of extensive licensed datasets, we innovatively employed transfer learning and even constructed a custom dataset using webcam footage, ensuring precision in the background elimination process.
Automating Comprehensive Reporting: Leveraging Google Looker Studio for Streamlined Analysis
For a long-standing client, we embarked on a project to automate their weekly and monthly reporting processes by harnessing Google Looker Studio. Formerly reliant on manually generated static reports, our adaptive solutions have significantly streamlined the client’s workflow.
Unlocking Financial Insights: Efficiently Identifying Top Global Speakers through Advanced Text Analysis
Tasked with discerning the top 10 global financial speakers from a vast dataset, we harnessed Named Entity Recognition (NER) to navigate 16,000 rows of textual data. Balancing accuracy and efficiency was key, leading to a rigorous data refinement process: eliminating low-quality entries, cleaning extraneous content, and focusing on relevant data with keyword filtering. The resulting extraction was not only accurate but also presented in an insightful format, providing the client with a comprehensive analysis of the speakers’ significance and impact in the financial domain.
Optimizing Financial Operations: Unraveling Data Patterns with CNNs
In an ambitious project, we developed a Convolutional Neural Network (CNN) aimed at recognizing intricate financial patterns, particularly reversals, in real-time data. With a goal to achieve over 75% accuracy and reduce dependence on the client’s resource-heavy supercomputer, our team ventured into the complexities of financial data analysis. Despite the initial challenges, such as the absence of labelled data and deciphering critical financial metrics, our relentless trial-and-error methodology led us to hit the desired accuracy. While not entirely substituting the supercomputer, the success of this model stands testament to our commitment and adaptability in confronting intricate data challenges.
Enhancing Tennis Match Predictions: A Leap from 69% to 91% Accuracy
Tasked with improving the prediction accuracy of tennis match outcomes, our team tackled a substantial yet cluttered dataset of 103 columns. Through meticulous data cleaning, feature engineering, and algorithm testing, we reduced the columns to the most pertinent 23. Despite challenges such as missing values and extraneous data, we leveraged the LSTM model to achieve a striking accuracy of 91%, significantly surpassing the client’s previous benchmark of 69%.
