Dash Sales Agent

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**DASH** turns raw, inconsistent General Trade sales exports into a clean queryable warehouse, a live dashboard, and a natural-language analyst — without ever letting an LLM write or execute code against your data.

Drop in a messy CSV. DASH works out what every column means, cleans it, files it away, and then sits on the dashboard writing chart captions, answering questions in plain English, and flagging numbers that look wrong.

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Why this exists

General Trade distribution data is painful in three specific ways, and DASH is built around each one:

Problem	What DASH does about it
Every export is different. Column names shift between ERP dumps. Three date formats turn up in one column. Names arrive as KRISHNA_TRADING_CO.	One LLM call classifies every column at once against a canonical schema, then deterministic Python does the actual cleaning.
Primary ≠ Secondary. What the company invoices to distributors and what distributors actually sell to retailers are different numbers, and nobody reconciles them.	Both are modelled as first-class tables with a built-in variance query that surfaces distributor inventory pile-up.
Every question needs an analyst. "Which produc