AI Sports Stats Automation | n8n Data Pipeline + Parent Dashboard An automated data pipeline buil...AI Sports Stats Automation | n8n Data Pipeline + Parent Dashboard An automated data pipeline buil...
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AI Sports Stats Automation | n8n Data Pipeline + Parent Dashboard
An automated data pipeline built in n8n that pulls sports statistics on a schedule, cleans and structures the data, and pushes it into a live dashboard for parents to track, with no manual data entry required.
The workflow handles scheduled triggers, API pagination, data transformation, and structured writes to the dashboard's data source, with retry logic so one failed request does not break the entire run.
Demonstrates the data engineering side of automation work: scheduled triggers, pagination, data cleaning, and dashboard-ready output, not only chatbots and lead generation.
Stack: n8n, REST APIs, Google Sheets and dashboard integration.
Some quick mockups for Relay, an AI infrastructure platform concept built around model routing, observability, and performance.
Exploring what a mobile command center could look like for teams managing multiple AI models, with a focus on clear data, fast decisions, and a developer-first UX.
Product design, mobile UI, AI tools, and a little systems thinking all in one.
Experimented a bit today with Krea and image generation for a case study I’m putting together around AI EarPods connected to OpenAI.
The focus has been on creating fashion-forward product imagery and art directing a world that feels specific to the identity, rather than just generating nice-looking AI images.
The trickiest part has been product consistency. Especially getting the EarPods to actually sit snug in the ear. If you’ve worked through this process, you probably know the struggle 😅
Simply telling AI to “make it fit more snug or in the ear” doesn’t always work. It loves to reinterpret the product every time.
Still experimenting, but getting closer. If anyone has found a good workflow for keeping products consistent across AI-generated shoots, I’d love to hear it!