Why AI companies need both raw and normalized customer data

Merge provides a unified API solution that facilitates the integration of hundreds of applications by normalizing and accessing both raw and normalized customer data, which is essential for optimizing AI capabilities. Normalized data is standardized and transformed for consistency, allowing for accurate, non-sensitive outputs in retrieval-augmented generation (RAG) pipelines, while raw data accommodates unique customer-specific information that may not fit strict normalization models. This dual data approach supports AI models by ensuring reliable outputs and contextually rich embeddings, thereby enhancing the performance of AI-driven products and features. Merge's platform, supporting over 200 cross-category integrations, uses predefined Common Models for data normalization and offers an Authenticated Passthrough Request feature to access raw data directly from customer systems, empowering AI companies like Guru, Ema, and Telescope to streamline their integration processes and improve their AI offerings.

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