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Information Retrieval From Emails

Every day, people send out hundreds of emails requesting private aircrafts for charter. On of our clients, True Aviation, wanted to connect people who had private aircrafts available along a specific route with people who wanted to travel on that route. For this, they required an interface that allowed

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Intelligent Document Processing

Our client wanted to use AI to automatically extract data from invoices and receipts. The extracted data can then be programmatically added to an accounting software such as Quickbooks. This eliminates the need for manual data entry - which is significant for larger companies that may need to process

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Soccer Analytics

One of our clients wanted to build an AI tool to analyse soccer matches and automatically derive insights that can help players identify the areas in which they need to improve. The goal was to build an AI tool capable of extracting detailed analytics from soccer match videos, including

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Automating Document Workflows for PropTech with IDP

The PropTech (Property Technology) industry is rapidly evolving transforming everything from property management and smart buildings to construction project delivery. Within this space, one of the most quietly impactful innovations is the adoption of OCR (Optical Character Recognition) and IDP (Intelligent Document Processing). As construction ...

Synthetic Data Generation with AI

High-quality data is crucial for training robust and accurate AI models. Traditional data collection methods, however, are often hindered by high costs, time constraints, and privacy concerns. Enter synthetic data generation—a revolutionary approach that addresses these challenges by creating artificial data for training AI models. This article explores the concept...

Graph Neural Networks: Modelling Complex Relationships in Data

Graph Neural Networks (GNNs) have emerged as a powerful tool in artificial intelligence and machine learning, offering novel ways to model complex relationships within data. Unlike traditional neural networks, which operate on fixed-size inputs, GNNs are designed to work with graph-structured data, making them highly versatile and applicable across various...

Safeguarding Digital Frontiers Through AI In Cybersecurity

In an era where digital threats are evolving rapidly, artificial intelligence (AI) has emerged as a critical component in fortifying cybersecurity measures. The increasing sophistication of cyber-attacks requires equally advanced defence mechanisms, and AI's capabilities in pattern recognition, predictive analysis, and real-time response are proving invaluable. This article looks...

AI in Financial Markets: Algorithmic Trading and Beyond

One of the areas in which Artificial Intelligence (AI) has found several applications is financial markets, where its influence is growing more pronounced. While the application of AI in financial markets is multifaceted, one of the most significant developments has been in the realm of algorithmic trading. Other than this,...

AI In Healthcare - Improving Diagnosis and Patient Care

The healthcare industry has undergone significant transformation through the integration of advanced robotics, machinery, and computer programs. Artificial intelligence (AI) has become a pivotal element across various sectors, and healthcare is no exception. By incorporating AI into healthcare systems, medical professionals can enhance the efficiency and accuracy of their services...

Retrieval Augmented Generation (RAG)

Large language models (LLMs) have significantly transformed the way we interact with information. However, LLMs have some limitations, one of which is that their training data, while enormous, may not include data that you want them to use while answering questions. For example, suppose that you run a financial consultancy...

AI-Based Credit Risk Assessment

Imagine that you are a lender (e.g., a bank), who frequently provides loans to different individuals and organisations. Each month you receive hundreds of loan applications, and you need to go through each of them to determine who to give the loan to. Naturally, you would prefer giving loans to...

Enhancing Farming and Agriculture Efficiency with AI

Because of advancements over the past decade, artificial intelligence technologies continue to change and impact various sectors and industries around the globe. One such industry is agriculture. By integrating sophisticated AI technologies, modern farms are becoming more adept at addressing complex challenges such as yield optimisation, resource management, and environmental...

The AI Software Development Lifecycle

The AI software development life cycle (AI SDLC) refers to the process of building and deploying artificial intelligence-based software applications. It encompasses various stages such as problem definition, data collection and preprocessing, model building and training, testing and validation, deployment, and maintenance. This structured approach ensures the systematic development of...

An Introduction to Machine Learning Operations

Machine learning has become a fundamental component in the tech industry, leading to the need for specialised operational strategies to manage ML production-grade systems efficiently. Machine Learning Operations, or MLOps, is a crucial practice that facilitates the seamless integration and operation of machine learning models within production environments. This article...

Automating Document Workflows for PropTech with IDP

The PropTech (Property Technology) industry is rapidly evolving transforming everything from property management and smart buildings to construction project delivery. Within this space, one of the most quietly impactful innovations is the adoption of OCR (Optical Character Recognition) and IDP (Intelligent Document Processing). As construction ...

The AI Software Development Lifecycle

The AI software development life cycle (AI SDLC) refers to the process of building and deploying artificial intelligence-based software applications. It encompasses various stages such as problem definition, data collection and preprocessing, model building and training, testing and validation, deployment, and maintenance. This structured approach ensures the systematic development of...

An Introduction to Machine Learning Operations

Machine learning has become a fundamental component in the tech industry, leading to the need for specialised operational strategies to manage ML production-grade systems efficiently. Machine Learning Operations, or MLOps, is a crucial practice that facilitates the seamless integration and operation of machine learning models within production environments. This article...

Enhancing Farming and Agriculture Efficiency with AI

Because of advancements over the past decade, artificial intelligence technologies continue to change and impact various sectors and industries around the globe. One such industry is agriculture. By integrating sophisticated AI technologies, modern farms are becoming more adept at addressing complex challenges such as yield optimisation, resource management, and environmental...

AI-Based Credit Risk Assessment

Imagine that you are a lender (e.g., a bank), who frequently provides loans to different individuals and organisations. Each month you receive hundreds of loan applications, and you need to go through each of them to determine who to give the loan to. Naturally, you would prefer giving loans to...

Retrieval Augmented Generation (RAG)

Large language models (LLMs) have significantly transformed the way we interact with information. However, LLMs have some limitations, one of which is that their training data, while enormous, may not include data that you want them to use while answering questions. For example, suppose that you run a financial consultancy...

AI In Healthcare - Improving Diagnosis and Patient Care

The healthcare industry has undergone significant transformation through the integration of advanced robotics, machinery, and computer programs. Artificial intelligence (AI) has become a pivotal element across various sectors, and healthcare is no exception. By incorporating AI into healthcare systems, medical professionals can enhance the efficiency and accuracy of their services...

AI in Financial Markets: Algorithmic Trading and Beyond

One of the areas in which Artificial Intelligence (AI) has found several applications is financial markets, where its influence is growing more pronounced. While the application of AI in financial markets is multifaceted, one of the most significant developments has been in the realm of algorithmic trading. Other than this,...

Safeguarding Digital Frontiers Through AI In Cybersecurity

In an era where digital threats are evolving rapidly, artificial intelligence (AI) has emerged as a critical component in fortifying cybersecurity measures. The increasing sophistication of cyber-attacks requires equally advanced defence mechanisms, and AI's capabilities in pattern recognition, predictive analysis, and real-time response are proving invaluable. This article looks...

Graph Neural Networks: Modelling Complex Relationships in Data

Graph Neural Networks (GNNs) have emerged as a powerful tool in artificial intelligence and machine learning, offering novel ways to model complex relationships within data. Unlike traditional neural networks, which operate on fixed-size inputs, GNNs are designed to work with graph-structured data, making them highly versatile and applicable across various...

Synthetic Data Generation with AI

High-quality data is crucial for training robust and accurate AI models. Traditional data collection methods, however, are often hindered by high costs, time constraints, and privacy concerns. Enter synthetic data generation—a revolutionary approach that addresses these challenges by creating artificial data for training AI models. This article explores the concept...