https://store-images.s-microsoft.com/image/apps.14296.42ba6bae-722f-4b99-b7d4-a0a382adc420.b0467947-2a2c-469e-8cfc-e813b8bb3d0e.70ac1765-eea5-4138-86a8-695d0b76c122

Leonardo Forge2Know

od: LEONARDO S.P.A.

Suite for data valorization and AI model creation with integrated security and governance features.

Structured with 2 inter-operating but independent products, Forge2Know integrates modern technologies and proprietary modules, designed to ensure security, scalability and interoperability environments.
DataPlatform: provide tools to speed and simplify data governance, data ingestion and big data processing and presentation.
AIEngine: a platform for the governance of AI models in terms of Responsible AI, Repository (Model/Dataset), Serving, Active Monitoring, Experience
Collector and Benchmark Evaluation.

By integrating them, you get a complete and scalable platform that enables you to transform data into strategic value, optimizing governance, processing and adoption of artificial intelligence with high standards of security and interoperability.ig Data and AI responsibly while driving innovation and achieving business goals.


Main components:

  • Data Lake: A ready-to-use multi tenant secure platform for ingesting, storing and retrieving structured, semistructured and unstructured data of any size
  • Data Processing: Providing functions for real time and batch elaboration leveraging in-memory execution engine and horizontal scalability, parallel processing and also through vector db. Publish-subscribe capabilities, event management, scheduling and workload management as well as visual ETL (Extract Transform Load) and a Secure Query Engine further empower data processing capabilities.
  • Data Security and Governance: Implementing a single, secure and centralized reference point for data control. By leveraging search and discovery tools and connectors to extract metadata from any data source, it simplifies data lineage, data protection, analysis, and pipeline management, as well as accelerates ETL processes.
  • Model build: Set of tools and best practices aimed at developing and maintaining Machine Learning (ML) models reliably and efficiently.
  • Presentation: A module for visualizing and interacting with data through graphical data quality interfaces and business intelligence tools: tables, charts and other types of representations
  • AI Engine: The system ensures accuracy, maintaining context and ensuring ethical and regulatory compliance through a processing engine, an orchestration framework, an information retrieval and enrichment pipeline, and monitoring. It includes the following features: Cognitive Endpoints, AI Pipeline, Agentic Framework, Feedback, Model Repository & Marketplace, AI Serving, AI Monitoring.

Súhrnný prehľad

https://store-images.s-microsoft.com/image/apps.40434.42ba6bae-722f-4b99-b7d4-a0a382adc420.b0467947-2a2c-469e-8cfc-e813b8bb3d0e.ca1b740c-1370-444d-8230-3deba86be131