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AI architecture is a crucial factor in developing high-quality AI applications. Software engineering complements AI, particularly through RAG architecture, and an AI-first mindset combined with a robust architecture is essential for business success.

Understanding and acting on tabular data, such as CRM and ERP exports, SQL databases, Excel sheets and comma separated values, remains challenging for large language models. In this post we show how an agentic workflow can take on the challenge of understanding tabulated data.

An AI engine acts as a versatile toolkit, enabling businesses to automate tasks previously requiring human intellect. It transforms messy data into structured, actionable insights, streamlining business processes and enhancing decision-making speed.

Deploy Qdrant to Azure with HTTP/2 and gRPC and access it asynchronously via a singleton instance of the Qdrant client via FastAPI dependency injection.