DataFlow Sheets

DataFlow Sheets represents a paradigm shift in data engineering, moving away from static grids toward dynamic, flow-based data processing within a spreadsheet-native environment. Built on a serverless architecture that bridges the gap between traditional spreadsheets and complex ETL (Extract, Transform, Load) pipelines, DataFlow Sheets allows users to integrate Large Language Models directly into cell logic. Its core engine, optimized for the 2026 data landscape, treats every row as a potential trigger for an autonomous workflow. By decoupling the execution engine from the interface, it supports high-throughput data enrichment, real-time web scraping, and multi-model AI synthesis (utilizing GPT-5, Claude 4, and proprietary local models). The platform is designed for growth-oriented organizations that require the flexibility of Excel with the power of Python-based data engineering. It specifically addresses the 'data bottleneck' in AI implementation by providing a governed, traceable environment for prompt engineering and data cleaning at scale, ensuring that enterprise data is structured and vectorized for RAG (Retrieval-Augmented Generation) systems before it ever leaves the sheet.