Meguri
All Projects
Next.js Convex TypeScript

Meguri

SmartStock for recipe-based businesses and small retail

01

Overview

Meguri is a smart stock and demand forecasting app for recipe-driven businesses and small retail teams. It keeps workspace, inventory, recipes, sales, suppliers, purchase planning, alerts, and forecasting in one operational system so daily work stays visible and controlled.

02

Problem & Solution

The Problem

Small businesses often manage stock in spreadsheets or manual workflows. That makes stock movement hard to track, connects sales to recipes or BOMs poorly, delays purchasing, and increases the chance of stockouts or waste.

The Solution

Meguri solves this with a workspace-scoped app built on Next.js and Convex, with real authentication, inventory CRUD, stock movement audit logs, sales tied to recipes, supplier and purchase planning, alerts, and forecasting or reorder recommendations based on live system data.

03

Tech Stack

Next.js 15 + React 19

Provides the app shell and interactive UI layer for the main workspace, dashboard, inventory, forecasting, alerts, and planning pages.

TypeScript

Keeps the data model, query handlers, and UI contracts explicit across the repo, which matters for workspace-scoped business logic.

Convex

Acts as the backend, database, and realtime query layer for inventory, sales, supplier data, alerts, and forecasting snapshots.

Better Auth

Handles authentication and session management so workspace access control can be enforced reliably.

Tailwind CSS 4

Provides the styling system for the dashboard, navigation, and operational pages without adding heavy custom CSS overhead.

Motion, lucide-react, Iconify

Supply the UI motion and icon set used to keep the experience clear, modern, and easy to scan.

04

Key Features

  • Multi-tenant workspace model with role-based access control
  • Inventory management with add, edit, archive, adjustment, and movement history
  • Product and recipe/BOM mapping to connect finished goods with ingredients
  • Sales transactions that deduct stock from recipes and preserve an audit trail
  • Supplier management and purchase planning through reorder recommendations
  • Forecasting dashboard with 7, 14, and 30 day snapshots plus manual refresh
  • Alerts for low stock and unusual demand
  • Dashboard pages for inventory, products, sales, forecasting, suppliers, reports, and settings
05

Challenges & Learnings

#01

Workspace scoping and permissions

Every query and mutation has to stay inside the correct tenant boundary so data cannot leak across workspaces or bypass role-based permissions.

#02

Forecasting and recommendation quality

The current forecasting layer uses moving averages from stock movement data, which works for the MVP but will need stronger forecasting logic over time.

#03

Idempotent reorder generation

Purchase recommendations need to be regenerated safely without creating duplicate pending records, so existing recommendations are cleared before a new run.

#04

Production readiness gaps

The roadmap still calls out work such as deployability baseline, supplier PO flow, reports and export, onboarding, and multi-location support before production hardening is complete.

06

Screenshots

Meguri dashboard overview

Meguri dashboard overview

Meguri product creation modal

Meguri product creation modal

Meguri inventory list

Meguri inventory list

Meguri recipe and BOM screen

Meguri recipe and BOM screen

Meguri sales log

Meguri sales log

Meguri forecasting view

Meguri forecasting view

Meguri supplier management screen

Meguri supplier management screen

Back to all projects Source link not available