A self-briefing data warehouse

Six disconnected platforms unified into one source of truth, with daily and weekly briefings written from real figures, not guesses.

Data and Analytics→

Problem

A high-volume direct-to-consumer brand ran on six disconnected platforms: its online store, a marketplace, email and SMS, web analytics, a KPI dashboard tool, and video. The CEO and COO had no single trustworthy view, assembling one by hand ate real time, and pipelines could fail quietly, so a report could look complete while data was missing underneath.

Build

A modular pipeline pulls all six sources nightly into one warehouse, storing raw data atomically so nothing is lost to early summarizing. On top sits an AI intelligence layer built in n8n: a deterministic metrics engine pre-computes every figure and comparison, then an LLM turns it into a daily briefing for the CEO, a weekly one for the CEO and COO, and an on-demand chat agent that answers questions straight from the warehouse.

How it works

The hard part was trust, not extraction. A pipeline can report success while quietly dropping data, so the system never lets a green checkmark stand in for the truth: it tracks freshness per source, flags anomalies with z-scores against each metric's own baseline, and tells the model which sources are stale so it skips them instead of inventing numbers. The metrics engine does the math deterministically; the model only interprets, so the briefing reasons over real figures rather than guessing them.

Outcome

/The work of a data analyst, an operations coordinator, and a reporting assistant is compressed into a briefing that lands every morning.
/Six tools that never talked to each other resolve into one trustworthy view.
/Silent data gaps surface instead of hiding behind a pipeline that looks healthy.

At a glance