*2. The Problem (Why now?)* Specialty coffee shops struggle to increase their average order value (AOV) because they lack digital tools to suggest pairings. Currently, menu data is "trapped" in PDFs, static websites, or Instagram images. Manually entering this data into a system is a bottleneck that prevents scaling.
*3. The Solution (How it works)* We build a bridge between B2B inventory and B2C taste. Our platform uses:
- *Automated Crawling:* Pulls data from shop URLs/socials. - *Computer Vision/NLP:* Standardizes messy menu items into a structured pairing-ready format. - *The Engine:* A hybrid ML/Rule-based system that suggests the perfect pastry for every bean profile.
*4. My Background (The Non-Tech Value)*
- *Domain Expertise:* Deep understanding of the specialty coffee B2B landscape. - *Customer Validation:* (Mention if you have spoken to X shops or have a waitlist). - *Execution:* I handle sales, marketing, and the B2B dashboard logic. I need a partner to own the data extraction and recommendation pipeline.
*5. What I’m looking for in a Co-Founder* A *Full Stack Engineer* who is excited by:
- Web scraping at scale. - OCR and NLP pipelines (turning images of menus into data). - Building "scrappy" MVPs that solve real problems for small businesses. - Ideally, a fellow runner or coffee lover who values high-intensity work and clear communication.
Personal: Achievement of 50 half marathons last year while managing a full-time project
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