Context
The client problem was not only “find creators”. It was turning discovery, enrichment, filtering and outreach preparation into one repeatable system across Instagram, TikTok and YouTube.
Architecture that mattered
The system used a staged processing model: discovery, profile enrichment, screenshot generation, filtering, evaluation, contact extraction and finalization. That matters because the data needed to become more trustworthy at each step, not just larger.
Delivery shape
- Multi-platform discovery instead of one-source dependency
- AI evaluation layered on top of structured data and screenshots
- Campaign-oriented operating model with exports and database storage
- Additional analytics enrichment for selected channels
Why it belongs in the portfolio
This case is a good example of combining backend work, data operations and AI-assisted workflow design without pretending the model itself is the product. The value came from the workflow structure and the operator experience around it.
Outcome
The repository documents a seven-step process and a throughput-oriented analytics stage, including eight concurrent workers and roughly one hundred sixty channels per minute for a follow-up tracking flow. That is exactly the kind of operations-aware detail buyers care about.