Activity Discovery AI Agent
AI-Driven Architecture for Platform Discovery, Structured Extraction, and Automated Processing
Community activity information is scattered across thousands of websites, making manual discovery, extraction, and validation slow, inconsistent, and difficult to scale.
This whitepaper presents an AI-driven, cloud-native architecture that automates the complete activity discovery lifecycle, from platform identification to structured activity processing and database integration.
What You'll Learn
By downloading this whitepaper, you will discover how to:
- Build an AI-powered pipeline for discovering activity-hosting platforms across cities, states, and neighborhoods.
- Automatically identify listing pages that contain relevant activity information.
- Extract structured activity data from both static and JavaScript-rendered websites using Firecrawl, Playwright, and GPT models.
- Validate, enrich, and standardize activity records for downstream applications.
- Filter activities based on senior relevance using an independent AI evaluation layer.
- Improve activity discoverability through neighborhood mapping, duplicate detection, and automated image generation.
- Design a scalable, serverless architecture using AWS Lambda, Amazon SQS, Amazon S3, and cloud-native services.
Download the whitepaper now to discover how AI automated end-to-end activity discovery and processing.
