Where does EASL work within the AI/ML ecosystem?

EASL prepares the data foundation that AI systems rely on. The platform can ingest structured, semi-structured, and unstructured sources, extract relevant fields, apply consistent logic, and deliver clean outputs wherever they’re needed. AI teams use EASL to support:

• Vector databases that depend on accurate and up-to-date embeddings
• RAG pipelines that require well-organized context windows
• Feature stores that break when upstream definitions drift
• Training environments where stable inputs shorten iteration cycles

Because EASL adapts as business rules change, teams spend less time rebuilding prep steps and more time advancing their models. Learn more about how EASL supports high-variability AI workloads on our AI/ML page.