Our Data Scientists & ML Consultants offer end-to-end Machine Learning, Data Science, AI & software development services. Our team has experience delivering solutions for each step of the ML development lifecycle from data integration & feature engineering to deployment of scalable ML & AI solutions both on-premise and in the Cloud.

Our Focus Areas

We specialize in solving Computer Vision, Natural Language Processing, Signal Processing and Predictive Analytics problems for Healthcare, Retail, Manufacturing, Travel, Banking and Public sector entities.

• Natural Language Processing: From information extraction to topic modelling and named-entiy recognition, our team has developed a range of NLP solutions using open-source frameworks as well as Cloud solutions such as Amazon Comprehend and Amazon SageMaker.
• Computer Vision: We have experience in solving object detection, image classification, and sementic segmentation challenges using open source technologies like TF/Keras, PyTorch, CUDA as well as computer vision Cloud services like Amazon Rekognition and Microsoft Azure Computer Vision API.
• Predictive Analytics: We have helped our clients leverage their transactional, customer, and market data to predict future sales, cutomer churn and better understand their markets.

Our Approach

Our approach involves working backwards from our customer's requirements and identify the right data points and solution that can best solve their challenges. Our process involves:

• A Customer Workshop: One of our experts will conduct a workshop with you spending 3 days working backwards from your requirements, understanding current challenges and whiteboarding the potential solution. The workshop is preferrably done on-site and involves problem formulation, defining an MVP and developing a product/project roadmap.
• Data Integration & Exploration: The success of a Machine Learning project depends on availability of clean, relevant and up-to-date data. Our expertise in Data & Analytics, combined with our Data Science team's experience in data profiling and feature engineering, allows us to set the stage for the development of effective and reliable models.
• Model Development: Our Data Scientists have extensive experience of developing models using differeent algorithms and network architectures, comparing model performance, running experimeents in parallel using HPO techniques, and optimising model performance. We also have worked with Cloud AI/ML solutions, which we believe allows for rapid model development at a fraction of a cost while leveraging the scale and efficiency of the cloud.
• Application Development: Our Software Engineering team works hand-in-hand with our Data Scientists to ensure the models are integrated into the target solution whether it be in the form of a front-end being exposed to the end-user or a REST API published for use by third-parties or other downstream system. Their focus is on the packaging of the application through containerization, development of secure APIs, scalability of the application and overall application security.
• Deployment & Maintenance: Our Engineering team have worked with our Data Scientists to develop continuous integration and automated deployment processes for the ML solutions both on-premise and in the cloud. Our team's DevOps experience puts them in a strong position to help the clients get the best out of their solution in terms of scalability, availability and manageability.