3 steps to improve Test Data Management. Download Gartner's report.
Large Language Models (LLMs) are poised to become one of the most advanced AI technologies within the next 1 to 3 years. These models will continue to be optimized, improving accuracy and refinement capabilities through pre-trained systems. Organizations will have the flexibility to run these models internally or leverage external providers, enabling icaria Technology to integrate and benefit from these advancements.
Users will progressively become accustomed to interacting with these technologies (empowering global organizations through ChatGPT and OpenAI).
At icaria Technology, we are committed to integrating AI at all levels—both in our products and within our teams. However, our vision is not to replace human expertise but to enhance efficiency, optimize workflows, and improve project success rates.
From the early days of icaria TDM, we have identified data model documentation as a critical challenge. Understanding data domains, relationships between tables, and their functional behavior is essential, yet documentation is often incomplete or outdated. This insight emerged from icaria Lean Factory, our Low-Code MDA solution, where the data model serves as the foundation for application development.
In the realm of Test Data Management (TDM), synthetic data is often directly associated with generative AI. While this idea is promising in theory, the reality in the applications managed by icaria Technology, and specifically in icaria TDM, is more complex. These applications operate in highly complex environments where error tolerance is minimal, and current technology, both in the short and medium term, is not yet fully capable of addressing this challenge.
However, generative AI has proven to be highly effective in certain specific scenarios. It is particularly useful for interpreting small-scale records and value spaces, as well as generating reduced test data, such as multi-level JSON structures or datasets with a limited number of tables. While generative AI is not a universal solution for all icaria TDM needs, it presents significant opportunities in contexts where scale and complexity are manageable.
icaria Technology’s AI initiatives focus on enhancing data governance, TDM, and GDPR compliance, including:
The vision of icaria Technology is being materialized through a series of concrete initiatives across key areas:
AI-driven identification of critical data locations within the system.
Automatic detection of dependencies & data structures for deeper insights.
Interactive AI tool for querying and analyzing metadata conversationally.
AI-driven identification of technical rules to enhance automated testing.
Several of these initiatives have already been implemented, with significant advancements in:
At icaria Technology, we are constantly researching, testing, and refining our AI-driven solutions. As technology evolves, so do our initiatives—ensuring we remain at the forefront of AI-powered Test Data Management.
Stay tuned for more breakthroughs as we push the boundaries of AI in test automation and data governance.
If you have questions or want to learn more about how our tools can transform your processes, feel free to reach out to our team!
