Data modeling for reliable AI
A semantic layer brings precision and reliability to AI by serving as a link between raw data and applications.
Many organizations struggle with bringing together large amounts of data that are often scattered across legacy systems, relational databases, and cloud platforms. That's why we design a semantic layer tailored to your organization, based on ontologies and taxonomies. This creates a solid foundation for your AI solutions, without costly system migrations.
Responsible use of AI
Responsible use of AI is essential to comply with laws and regulations (such as the European AI Act) and compliance rules. Semantic layers offer a glass box instead of a black box solution, so that AI output is accurate, transparent and traceable. They use models such as ontologies and taxonomies to ensure that data is consistent and understandable to technology.
- Ontologies: Structured representation of knowledge that defines concepts within a specific domain and describes relationships between these concepts. It helps to make data understandable and consistent so that technology can effectively interpret and use it for AI applications.
- Taxonomies: a hierarchical division of concepts within a given domain, dividing broader categories into smaller, more specific subcategories. It offers a structured way of organizing knowledge, making data easy to understand.
.png)
What is a semantic layer?
A semantic layer ensures that AI understands nuances and correctly applies data in various situations within your organization. It forms a link between raw data and applications, so that data is interpreted meaningfully and in the right context.
For example, “salary” in the definition for HR can also include fringe benefits, while Finance defines it differently. This is very relevant for reliable AI output.
Transparent and traceable AI
Make the most of your data by integrating and standardizing it, regardless of the source. We help you translate data into meaningful structures. By making data accessible and understandable, you can use your organization's full data potential without complex migrations.
- Transparency: Semantic models ensure that the meaning of data is clear and consistent.
- Semantic structures: Using well-defined ontologies and taxonomies helps ensure data reliability.
- Data integrity: Semantic models ensure that data is stored and processed in a consistent and structured way.
- Legislation and regulations: Semantic models support accountability under the AI Act, GDPR and sector-specific rules.
Want to know more? Get in touch!
from AI or do you want a free demo of Ally™?