1. Introduction

Nimbus is an open-source framework designed to simplify the deployment of lightweight, task-specific Natural Language Processing (NLP) models into production. While these models can offer valuable insights, getting them deployed typically requires significant cloud expertise, infrastructure setup, and ongoing maintenance, barriers that many individuals or small teams can’t afford to overcome.

Nimbus solves this by automating the most challenging parts of deployment through a simplified workflow and CLI. It turns trained models into scalable, production-ready services without requiring proficiency in DevOps or machine learning infrastructure.

This case study details the real-world challenges of deploying NLP models, how Nimbus addresses those challenges, and the technical decisions that shaped the framework’s design. Finally, it also outlines opportunities for future development and broader applications.