Live

BrewMatch

Personal coffee discovery shaped around taste.

BrewMatch logo.

Problem

Why BrewMatch exists.

Buying coffee is surprisingly hard. Flavor language varies by roaster, recommendations are often generic, and people end up choosing beans with very little confidence.

People want better coffee, but most recommendation experiences assume they already know the vocabulary. BrewMatch exists for the moment before expertise, when someone knows what they enjoy but not how to translate that into a good bag of beans.

Solution

Designed to make the next step clear.

BrewMatch turns personal taste, brewing habits, and caffeine preferences into a short, useful set of recommendations. It explains choices in plain language so discovery feels guided, not technical.

Home brewers, gift buyers, and curious coffee drinkers who want practical guidance without becoming experts first.

Key features

Small surfaces, clear intent.

Taste Matching

Translate everyday flavor preferences into practical coffee recommendations.

Brewing Preferences

Tune suggestions around pour-over, espresso, French press, or daily drip routines.

Caffeine Preferences

Respect strength, roast, and energy preferences without making the choice clinical.

Bean Discovery

Surface beans that fit the drinker instead of overwhelming them with inventory.

Brewing Tips

Offer small guidance moments that make the first cup more likely to succeed.

Technology

Engineering in service of clarity.

Next.js

Fast product surface with static routes and responsive rendering.

TypeScript

Typed product logic for recommendations and preference modeling.

Preference engine

Taste signals are mapped to useful coffee attributes.

Responsive design

Built for quick discovery on phone or desktop.

Current status

Live

The product is moving toward richer roaster inventory integrations and clearer side-by-side comparison views.

Next step

See the product in its own environment.