Track applications, score job matches, and generate professional documents. Self-hosted on your own server, completely free.
Save time
10+ hours/week
Works for
All professions
Setup time
< 2 minutes
Applications scattered across emails and spreadsheets. Hours spent rewriting the same documents. No idea which roles to prioritize.
Stop losing track of applications. Organize every opportunity, see how well you match each role, and create tailored documents that get responses.
Your job search reveals salary expectations, career goals, and personal details. Keep that data under your control.
Your data never leaves your server
Free forever, no hidden costs
Modify, extend, or audit the code
See how well you match each role and create tailored documents that get responses
See everything at a glance. Track status from 'Interested' to 'Hired' in one dashboard.
Know your real chances. AI analyzes each role against your profile and shows a compatibility score.
Professional documents in 30 seconds. Each one customized to the specific job requirements.
Get started with one Docker command
One Docker command. No complex setup.
Enter your experience once. Use it for every application.
Add jobs via browser extension or manual entry. Stay organized automatically.
Enhance your Vega AI experience with our browser add-on. One click captures job details directly into your self-hosted platform.
Transform any job board into your personal assistant. The Vega extension adds a capture button to job listings, instantly saving them to your self-hosted platform.
Installation instructions are included in the setup guide.
TechCorp • Remote
No tracking, no analytics, no subscription traps.
Requirements:
Docker + Google Gemini API key
Deploy on a Raspberry Pi, basic VPS, or old laptop
Set up Vega in minutes with Docker and begin navigating toward your dream career
Get your free Gemini API key, then follow these steps:
Step 1: Create a vega-ai folder
mkdir vega-ai
Step 2: Create a config file with your settings
Create a file called config in the vega-ai folder with this content (replace your-gemini-api-key with your actual key):
GEMINI_API_KEY=your-gemini-api-key
CREATE_ADMIN_USER=true
ADMIN_USERNAME=admin
ADMIN_PASSWORD=your-secure-password
Navigate to your vega-ai folder and start Vega with persistent data storage:
docker run --pull always -d \
--name vega-ai \
-p 8765:8765 \
-v vega-data:/app/data \
--env-file config \
ghcr.io/benidevo/vega-ai:latest
Visit http://localhost:8765 and log in with your admin credentials.
Add the browser extension for one-click job capture:
chrome://extensions/
Common questions about Vega AI
Download the extension ZIP from GitHub releases, unzip it, then load it in Chrome at chrome://extensions/ with Developer mode on. Click the Vega icon, configure your connection (usually localhost:8765), and you're set. Your Vega backend needs to be running first.
Just browse LinkedIn job listings. The extension adds a capture button on each post. Click it, add notes if you want (salary expectations, interest level), and save. All job details are extracted automatically. No manual copying needed.
Try these steps: Check you're signed in (click the extension icon). Test your connection in settings. Make sure you're on a LinkedIn job page and the backend is running. Still stuck? Refresh the page or check the extension is enabled at chrome://extensions/.
Basic Docker knowledge is helpful but not required. If you can follow simple command-line instructions, you can set up Vega AI. You can install Docker on Windows, Mac, or Linux. The actual job tracking interface is as easy to use as any web app.
Google Gemini provides the AI capabilities for job matching and document generation. You can get a free API key from Google AI Studio. The free tier is generous enough for personal job searching. You get 60 requests per minute for free.
Yes! Vega AI works for any profession: developers, designers, teachers, analysts, managers, and more. The AI adapts to your specific field and experience level.
Absolutely. Vega AI runs entirely on your own server. Your job search data, salary expectations, and personal information never leave your control. Only the AI prompts go to Google Gemini for processing.
The Vega AI community is active on GitHub. You can open issues, ask questions, or contribute improvements. Since it's open source, you can also modify it to fit your specific needs.
Absolutely! Vega AI runs perfectly on your personal laptop or desktop. No need for cloud providers or monthly hosting fees. Just install Docker and run it locally. Your job search data never leaves your machine.
Vega AI uses less than 50MB of RAM, making it incredibly lightweight. You can run it alongside your other applications without any performance impact. It even works on older computers, Raspberry Pis, or a $5/month VPS if you prefer remote access.
Stop the container, update your password in the config file, then add RESET_ADMIN_PASSWORD=true and restart.
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