AutoParts AI Copilot

Automotive parts support for the UAE and Saudi Arabia, built around Telegram, n8n, and retrieval-augmented generation (RAG).

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01 / Overview

Project context

An owner-built workflow and integrations for automotive parts support in the UAE and Saudi Arabia, described as using Telegram, n8n, and retrieval-augmented generation (RAG).

Workflow and integrations built by the owner.

02 / Workflow evidence

Architecture, as documented

Inspect the authentic, uncropped workflow capture. The image documents a configured canvas, not verified runtime behavior.

Owner-supplied workflow capture · Auto Parts – Telegram RAG · Select to enlarge

Owner-supplied workflow screenshot for Auto Parts – Telegram RAG. — Owner-supplied workflow capture · Auto Parts – Telegram RAG · Select to enlarge

The available project evidence supports the description on this page, but not a separate reconstructed architecture diagram. The original workflow capture remains available above.

03 / Implementation record

Tools, data & engineering notes

Data

Experimental Excel data

Tools

Telegram
n8n
RAG

Engineering notes

Auto Parts – Telegram RAG and Auto Parts – Ingestion are owner-confirmed workflows within this project.
The available authentic screenshot documents Auto Parts – Telegram RAG. No separate Ingestion screenshot is present.

Confirmed workflows in this project

Auto Parts – Telegram RAG
Auto Parts – Ingestion

04 / Evidence boundary

What the evidence supports

Current evidence

Owner-supplied project context and the repository’s authentic Auto Parts – Telegram RAG workflow capture.

Limitations

The data is experimental Excel data, and supplier integrations are incomplete.
The available evidence does not establish live supplier data, verified fitment, production readiness, or measured results.