Project: Release Notes v1.0

Date: July 7, 2025

What's New in This Release

This first release introduces the core functionalities of the Essedum platform, enabling users to connect to various data sources, build and manage AI/ML pipelines, and deploy models seamlessly.

Key Features:

• Connections: Establish a communication link or interface between different software systems. This allows for the exchange of data, the ability to perform actions, and access to resources from various environments.

• Datasets: Ingest and manage training data from a variety of sources, including Storage Buckets, MySQL databases, and REST APIs. This flexibility is crucial for building robust AI models.

• Pipelines: Create and manage both training and inferencing pipelines. These pipelines are essential for fine-tuning, training, deploying, and registering models as endpoints.

• Models: Access and manage all your models from configured connections. Essedum supports a wide range of MLOps platforms including On-Premise servers, AWS SageMaker, Azure ML, and GCP Vertex AI.

• Endpoints: View and manage all endpoints from your connected services. This includes REST APIs, model endpoints, and more, providing a centralized view of your deployed services.

• Adapters: Integrate and utilize various services and capabilities of endpoints without needing to provide host details. Adapters simplify the process of interacting with different services.

• Remote Executor: Execute pipelines or programs on a remote server or virtual machine. This powerful tool allows for the efficient use of computational resources for demanding AI/ML tasks.