chaM3Leon – MLOps Framework for AI/ML and Big Data Pipelines
chaM3Leon – Framework MLOps for AI/ML and Big Data
Artificial intelligence has enormous potential, but turning it into real solutions requires complex and often costly infrastructures. chaM3Leon was created to simplify this journey: an open-source framework that reduces the time and resources needed to build data pipelines, making them traceable, scalable, and easy to put into production.
Thanks to an architecture inspired by the Lambda model and modular components for batch processing, streaming, and machine learning algorithms, chaM3Leon enables a smooth transition from idea to result, quickly and efficiently. The goal is to make room for innovation, freeing users of the platform from technical complexity and allowing them to focus on generating real value.
/ Driving Efficiency and Productivity
chaM3Leon removes the need to build complex infrastructures from scratch: pipelines are ready to run out of the box, reducing time, costs, and reliance on specialized skills. Value is delivered faster—and with it, a competitive edge.
/ Built for Scalability
Built on technologies designed for big data, the framework grows alongside your project. Whether dealing with small datasets or massive real-time streams, the architecture remains stable and adaptable—cloud-ready and prepared for data-intensive scenarios.
/ Flexibility and Customization
Every pipeline can be tailored to fit your needs: from full support with expert consulting, to direct use of the open-source version, all the way to guided creation through the Workflow Designer. In every case, the result is a solution that aligns 100% with your specific requirements.
/ The Challenge
Bringing artificial intelligence into complex domains—from climate change to industrial processes—has never been easy. One of the biggest challenges is data traceability: tracking the origin of information and following every transformation is often impossible, which undermines trust in models and the ability to reproduce their results. Adding to the difficulty is data quality: information comes from fragmented sources, in different formats, and with varying levels of reliability. Integrating and validating it becomes a long, costly, and error-prone task. Finally, there is the issue of scalability and cost: building AI and big data pipelines from scratch means dealing with complex projects that demand significant time, specialized expertise, and heavy investments. All of this slows down the adoption of innovative solutions precisely in the contexts where they are most needed.
/ Smart Shaped’s Solution
To address these challenges, we developed chaM3Leon, an MLOps framework designed to make building AI and big data pipelines simpler, faster, and more secure. At its core lies a “traceability-first” approach, embedding data traceability directly into the design to ensure transparency and trust in the results.
The architecture, inspired by the Lambda model, combines components for both batch and real-time processing with a custom data collection module and a dedicated machine learning layer. Everything is orchestrated through Apache Airflow, ensuring workflows that are clear, scalable, and easily replicable.
chaM3Leon is flexible and adaptable to different scenarios: it can be adopted as an open-source solution, implemented with tailored consulting, or, in the future, leveraged through an intuitive Workflow Designer that allows pipeline configuration even without advanced technical skills.
The result is a platform that reduces development time and costs, accelerates the journey from idea to production, and makes artificial intelligence accessible and reliable—even in complex domains.
/ Project Objectives
The main goal of chaM3Leon is to bridge the gap between an idea and its realization. The framework enables the creation of data pipelines in a faster, safer, and more cost-effective way, allowing companies to focus on the value they generate rather than on technical complexity.
Its priorities are threefold:
Ensuring security and data integrity, also thanks to integration with blockchain technologies.
Boosting operational efficiency, reducing development time and costs with a modular and scalable architecture.
Guaranteeing regulatory compliance, embedding governance and traceability principles aligned with European standards (GDPR, EU GMP Annex 11, GAMP 5).
In this way, chaM3Leon positions itself as a solid and flexible tool, able to adapt both to research projects and to industrial and production environments.
Project Documentation
For those who want to explore further, comprehensive documentation is available, detailing the framework’s functionality, technical architecture, and tested use cases.
