Building a $300k AI-Orchestrated POS Telemetry Pipeline for Multi-National Retail Footprints

Описание и применение

Создана AI‑оркестрованная система телеметрии POS для международной сети розничных точек, автоматизировав сбор, очистку и анализ данных, что позволило точно измерять ROI маркетинговых кампаний.

Задача

Retail chains lack integrated data linking field marketing efforts to in-store transaction telemetry, causing attribution gaps and manual data cleaning.

Результат

Unified cross‑border POS data, automated 100% data cleansing, and enabled precise ARPU attribution, achieving a $300k ROI for the client.

Рабочий процесс

• Deploy React.js front‑end on in‑store tablets via Vercel edge network
• Expose GraphQL API on Node.js runtime
• Integrate OpenAI GPT via LangChain for data cleaning and PII sanitization
• Store cleaned JSON payloads in PostgreSQL
• Automate real‑time customer segmentation and ARPU calculation
• Deliver insights to client IT administrators

Доказательства

100% Data Cleansing Automation: Replaced manual administrative entry with automated LangChain/GPT workflows, dropping data pipeline ingestion error rates to near zero.

Источник

The project was delivered under the strict operational guidelines of the Granton Group’s global Standard Operating Procedures (SOPs).

Источник