Artificial Intelligence and Machine Learning (AI/ML)
QuietGrowth Tech data scientists and data engineers have built innovative features using AI/ML for various tech products. Below is the high-level information on our team's AI/ML activity.
Prediction engines
Develop prediction engines using supervised machine learning algorithms that can estimate an appropriate set of actions based on the insights identified from the collected historical information.
We built this capability for: A fintech product and a healthtech product.
Novel techniques using statistical models
Research and development of novel techniques related to health and fitness by building statistical models based on the study of new insights discovered by the community and using evidence-backed data science methodology.
We built this capability for: A healthtech product.
OpenAI powered Vector Search system
Implement advanced vector search systems powered by OpenAI's generative models. These GenAI-powered systems enable highly accurate and context-aware searches, retrieving relevant information from vast datasets while generating insightful responses.
We built this capability for: A knowledge management product.
Contextual Search driven by Hugging Face LLMs
Design and implement vector search systems enhanced with Hugging Face's state-of-the-art 'large language models' (LLMs). These systems excel in retrieving contextually relevant information and generating detailed responses based on the search results.
We built this capability for: A customer support product.
Advanced image processing systems
Build real-time advanced image processing systems for analysing videos and large sets of images. These systems use computer vision and statistical modelling techniques to perform different kinds of analyses on the image data. These analyses include segmentation of a region, pixel-to-pixel analysis and pattern matching.
We built this capability for: A healthtech product.
Bio-signal processing systems
Build a bio-signal processing system that collects the data from one or more biosensors and analyses the signals collected to calculate unique signal features. The intelligent system will then calculate health-related metrics using these signal features.
We built this capability for: A healthtech product.
We research and innovate to boost the intelligence of your products.