ever-co/ever-gauzy

Productivity & Utilities

An open ERP/CRM/HRM suite for small teams that want time tracking, invoicing and projects in one self-managed system.

8,592
1,297
TypeScript
AGPL-3.0
7 years old

Gauzy is a broad business-management platform assembled from modules most small companies otherwise stitch together from separate SaaS tools: time tracking, HR records, CRM contacts, project tasks, proposals, invoicing and accounting. It is worth a look if you run a services team and want that data in one place you control; it is a poor fit if you only need one of those modules.

The problem

A small agency typically tracks hours in one tool, keeps client records in another, raises invoices in a third and chases approvals over chat. Every handoff is a manual export or a copy-paste, and the same client exists under three different names. Gauzy puts employee time, project tasks, client contacts, estimates and invoices inside one organization, so a timesheet entry and the invoice line drawn from it live in the same system. The result is a single record of who worked on what and what it should be billed at.

What's different

The project's distinguishing choice is breadth rather than depth in any one module. The README lists HRM with onboarding and time off, an applicant tracking system, CRM, sales pipelines, proposals, accounting and invoicing, expenses, inventory, equipment sharing, goals and KPIs, plus multi-organization management and public organization/employee pages. For a small business, that means one login and one database of people, clients and money instead of integrations.

The mechanism behind it is a headless API-first design: the backend is NestJS with TypeORM/MikroORM, the frontend Angular, and the same API is available directly for custom clients API docs. That makes it feasible to build a narrow front end on top of it. The trade-off is the familiar one for suites: adopting Gauzy means committing to its data model for time, billing and contacts at once, and the README describes the hosted version as Alpha/testing, to be used cautiously.

Who should try it

A good fit is a services company or software studio of roughly tens of people that wants self-hosting, time tracking tied to projects, and invoicing derived from tracked hours. A poor fit is a single freelancer who just needs invoices, or a large enterprise that already has an ERP and only wants a time tracker; in both cases the surrounding HR, ATS and inventory surface is overhead.

If you want to evaluate without running infrastructure, the project points to a hosted instance at app.gauzy.co, but it is explicitly labelled Alpha/testing. Teams that prefer to inspect or extend the code can use the Gitpod environment linked from the README Gitpod setup; the same page covers the manual build path.

Requirements and limitations

The README recommends PostgreSQL or MySQL for production and Kubernetes or Docker for deployment; SQLite is the default but described as suitable for demos. Running it yourself therefore means operating a database and a container/deployment pipeline, which is normal for self-hosted software but not a one-command install for a non-technical team.

The licensing is the constraint most likely to affect a decision. The default is the Community Edition license, with separate Small Business and Enterprise licenses, and the project publishes a comparison page for the tiers license comparison. If Gauzy is central to a commercial workflow, check which tier applies before investing in migration. The README also states plainly that 100% security cannot be guaranteed and the software is provided as-is, so plan backups and HTTPS/WSS for any production use.

HotRepo's take

The only dated observation is a single day on GitHub's daily trending board on 2026-10-25, at 8,584 stars with +34 that day. With one recorded day and no earlier comparable history, persistence of interest cannot be judged from HotRepo's data; the repository itself dates to 2019. Before committing, read the tier comparison and confirm which license your use case falls under, since that, not the feature list, is what determines whether this is a practical replacement for your current stack.

Written by AI from the project's README, updated October 25, 2026. The project's own docs are the source of truth.