Training your own Large Language Model (LLM) requires robust and complex set of tools and technologies optimized for performance and cost. Training and inference can be very compute intensive and thereby expensive depending on the type of LLM being used. Moreover, LLMs are so new that proving a concept in the early stages is absolutely crucial in achieving success.

Cloud303 addresses these requirements by offering a comprehensive package that includes a pre-configured infrastructure on AWS to enable customers to train and infer from a Large Language Model on AWS utilizing the customer’s own data. Our solution streamlines the process of training and inference of an LLM by providing a standardized set of tools and frameworks on AWS.

• AWS SageMaker Pipelines initialized on AWS to process information (txt, pdf) uploaded and populate vector database.
• AWS Textract to extract text from PDF files uploaded.
• Assistance with tips on data to upload for better results.
• FrontEnd to upload, POC chat functionality, and Swagger endpoint to explore endpoint and integrate with existing applications.
• Free first 50,000 keywords extraction.