Artificial Intelligence / Machine Learning

Data Engineering

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At Lyteworx, we understand the importance of high-quality data in machine learning model development. That's why we specialize in automating the Extraction, Transforming, and Loading (ETL) process for massive amounts of data, ensuring it's ready for supervised learning applications. Our expertise lies in developing custom code to interact with APIs across multiple applications, enabling seamless data flow before and after labeling.

How We Can Help

Our ETL services enable you to:

  • Extract relevant data from various sources, including APIs, databases, and files

  • Transform the extracted data into a format suitable for machine learning model development

  • Load the transformed data into a database or file system for further analysis

By automating the ETL process, we help you:

  • Save time and resources by avoiding manual data processing

  • Improve data accuracy and quality through automated transformation and loading processes

  • Enhance your machine learning model development workflow by providing high-quality, well-organized data

Model Development

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We develop and deploy cutting-edge AI models for various applications. Our expertise spans multiple modes, including:

  • Computer Vision: We've produced Convolutional Neural Network (CNN) models for object detection on high-altitude imagery using the ResNet-50 architecture, starting from a pre-trained model using the Microsoft COCO dataset and finishing with the Cars Overhead With Context (COWC) dataset provided by the Lawrence Livermore National Laboratory.

  • Natural Language Processing: We've developed language models for text classification, sentiment analysis, and named entity recognition, leveraging frameworks like BERT and RoBERTa.

  • Time Series Forecasting: Our models have been trained on historical data to predict future trends, using techniques such as LSTM and Prophet.

Mode-agnostic Approach
We take an industry-best-practices approach by incorporating openly available, high-performance models into customer-specific applications. This process may involve:

  • Model Retraining: We retrain pre-trained models with custom data for fine-tuned performance in specific domains.

  • Transfer Learning: We leverage existing pre-trained models as a starting point and adapt them to new datasets and applications.

By partnering with Lyteworx, you can tap into our expertise in developing and deploying custom AI models that meet your unique business needs.