Dabstract Drops: Serverless Geolocation Product Locator

The Business Challenge Dabstract, a premium cannabis brand, operated on a standard Squarespace site but needed a highly dynamic, localized feature to show customers exactly where to find specific products and strains near them. Their internal team was already tracking inventory "drops" in a weekly Google Sheet, but they lacked the technical infrastructure to serve that data geographically to their end-users.

The Engineering Solution Rather than forcing the client to abandon their existing Squarespace setup, I architected a custom, serverless AWS backend and injected a dynamic web application directly into their static site. This bridged the gap between their manual internal workflow and a high-fidelity, interactive customer experience.

Automated ETL Data Pipeline: Engineered a highly reliable cron job using AWS CloudWatch to automatically extract the weekly drop data from their internal Google Sheets, perform complex data sanitization and reformatting, and load it into a high-speed AWS DynamoDB table.

Serverless Architecture: Built robust AWS Lambda functions exposed via API Gateway to handle real-time database queries and return strictly optimized HTML/CSS payloads directly to the frontend.

Geolocation Proximity Engine: Integrated native browser location sharing so the UI automatically calculates user coordinates against store locations, immediately rendering the closest available products, strain types, and exact distances to the user.

Dynamic Frontend Filtering: Built a seamless, real-time filtering interface embedded within Squarespace, allowing users to instantly query the database by zip code, store name, specific strain, or product category.

Tech Stack: AWS Lambda, AWS API Gateway, Amazon DynamoDB, AWS CloudWatch, JavaScript, RESTful APIs, Squarespace Integration.