AI-Ready Retail Database

Retail Data
Intelligence

A vendor data ingestion, processing, and standardization engine that handles both structured CSV uploads and complex unstructured documents — fully automated.

Azure OpenAI Claude Pulumi Azure Functions
10k+
SKUs Per Batch
100MB
Max File Size
1.0
Max Confidence Score
2
Processing Paths

The Challenge

Vendor data arrives in every format imaginable

Retail businesses deal with hundreds of vendors, each sending product data differently — clean CSVs, messy PDFs, multilingual catalogs, unstructured Excel files. Manually standardizing this is slow, error-prone, and unscalable. This platform automates the entire pipeline with two intelligent processing paths.

Architecture

Dual-Path Ingestion System

Depending on how data arrives, the platform routes it through one of two optimized paths.

Path A — Manual Template

Fast-track for structured data

Direct Upload Admin uploads a CSV following the strict schema.
Instant Validation API verifies data types and field constraints immediately.
Staged at 1.0 Confidence Records enter Products_Staging with maximum confidence.
Fast Track Bypasses AI entirely for maximum throughput.
Path B — AI Processing

Smart handling for unstructured docs

Raw Document Ingestion PDFs, catalogs, and Excel files uploaded to Azure Data Lake.
OCR & Extraction Azure Document Intelligence extracts tables and key-value pairs.
LLM Mapping Engine Claude & OpenAI map vendor fields to the product schema.
Confidence Scoring AI assigns 0.0–1.0; low-confidence items flagged for human review.
Template Memory Valid mappings saved — future uploads from same vendor are automatic.

Features

What the platform delivers

Built for reliability, scale, and flexibility at every stage of the pipeline.

⚡

Dual-Path Routing

Automatic routing to the right processing path based on file type and structure.

🧠

AI Field Mapping

Claude and OpenAI map arbitrary vendor fields to your product schema intelligently.

📊

Confidence Scoring

Every AI-processed record gets a confidence score so you always know what to review.

💾

Template Memory

Successful mappings are saved. Future uploads from the same vendor are fully automatic.

☁️

Infrastructure as Code

Entire infrastructure defined with Pulumi — reproducible, versionable, and auditable.

🔍

Validation Pipeline

Strict schema validation at every stage prevents bad data from entering production.

Tech Stack

Built on enterprise-grade cloud

Azure
Azure Cloud infrastructure & data lake
OpenAI
OpenAI LLM field mapping engine
Claude
Claude Document understanding & extraction
Pulumi
Pulumi Infrastructure as Code
Azure Functions
Azure Functions Serverless processing (Node.js)

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