Burrfect
Burrfect is an AI-assisted espresso shot tracker and recipe dial-in app for coffee enthusiasts who want better espresso recipes, automatic shot timing, bean context, and smarter recommendations.
Overview
The product story
AI espresso shot tracker for better dial-in workflows
Burrfect is an espresso shot tracker and recipe dial-in assistant built for people who want better espresso without wasting time, energy, or beans. The app helps users track shots, manage equipment, save beans, review recipes, and get smarter recommendations from their own setup and crowd-sourced espresso data.
My work focused on maintaining the Burrfect mobile app across Android and iOS while helping build new AI and machine learning features. The strongest technical feature is the espresso shot detector: an MFCC-based audio detection workflow that listens for espresso machine pump frequency and can automatically set the shot timer when a user starts pulling espresso.
Recipes, bean context, insights, and recommendations
Burrfect is not just a timer. The recipes feature lets users enter a bean name and roaster name, then fetches richer coffee context so the app can provide better starting guidance. The insights and recommendation features help users understand what happened in a pull, compare short and long pulls, and decide what to adjust next.
That combination makes Burrfect a more practical espresso assistant: it tracks the shot, understands the coffee, learns from the user’s setup, and gives next-step guidance that fits the actual dial-in workflow.
Challenge
Espresso users often track shots manually, guess when to start and stop timers, and lose context between beans, roasters, recipes, and tasting notes. Burrfect needed to make espresso dialing-in more automatic and more informed without making the mobile workflow feel technical.
Solution
Burrfect combines mobile shot tracking with AI-assisted recipe workflows, bean and roaster enrichment, community insights, and an ML-powered auto timer. The espresso shot detector uses MFCC-based audio analysis to recognize machine pump frequency, helping the app automatically time shots when the user starts pulling espresso.
How we did it
The important execution details
Maintained the Burrfect app across Android and iOS while shipping product improvements for espresso tracking, recipes, recommendations, and insight sharing.
Helped develop the ML-powered espresso shot detector using MFCC audio features so the app can detect espresso machine pump frequency and automatically control shot timing.
Worked on recipe workflows where users enter bean and roaster names, then Burrfect fetches richer coffee context to improve starting recipes and shot guidance.
Built and refined insight and recommendation features that help users understand short pulls, long pulls, balance, extraction, and what to change on the next shot.
Connected product work to Burrfect's store-positioned feature set: shot tracking, equipment management, bean reviews, smart bean data, crowd-sourced data, and AI/crowd-sourced recommendations.
Result
What the project delivered
Made espresso timing less manual by supporting automatic shot detection based on machine audio instead of relying only on user taps.
Improved the app's dial-in workflow by connecting bean, roaster, recipe, equipment, insight, and recommendation data in one mobile experience.
Supported a production Food & Drink app available on both the App Store and Google Play.
Helped move Burrfect toward a more intelligent espresso assistant that can guide users before, during, and after each shot.
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