Rebrowse is self-learning browser recorder.
It records what people browse, generates agentic browser workflows.
So users can execute them on cloud browser in one click.
Most AI copilots are terrible at workflow automation. They are
- slow - "what takes so much time?"
- not deterministic - "you did this yesterday. Don't you remember?"
- low visibility - "what is happening?"
- call LLM thinking at every run - "dude, you think too much."
I'm solving these real problems.
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Screen-recording + voice = AI workflows:
- Create one deterministic workflow at first.
- Yopu can visually understand the flow with condifence.
-
20x Speed and 95% Accuracy
- we use deterministic executions + customised flash-mode of browser-use.
- It allows us to execute at 20x speed.
-
The world-first real-time Preview/Evals of headless browser 🙈
- I used rrweb to ovecome CROS issues.
- You can interact in real-time with the remote browser deployed under proxy on cloud.
go to https://app.rebrowse.me
rebrowse-app
L api/ # Web backend server on 127.0.0.1:8000
L ui/ # Web frontend server on 127.0.0.1:5173
L extension/ # Rebrowse Recorder Chrome extension.- quick start with shared workflows.
- good for learning how to use.
# 1. Clone the repository
git clone https://github.com/zk1tty/rebrowse-app.git
cd rebrowse-app
# 2. Update .env with your credentials:
# - OpenAI API Key: https://platform.openai.com/api-keys
# - Supabase credentials: https://supabase.com/dashboard
# 3. Start the application
bash docker/setup-docker.sh
# 4. Access the application!
# Frontend: http://localhost:5173
# Backend API: http://localhost:8000- Docker Containers
- Start with a fresh workflow database.
- good for Entreprise test.
# 1. Clone the repository
git clone https://github.com/zk1tty/rebrowse-app.git
cd rebrowse-app
# 2. Update .env with your credentials:
# - OpenAI API Key: https://platform.openai.com/api-keys
# 3. Run setup script with self-hosting flag
bash scripts/setup-docker.sh --self-host
# 4. Access the application!
# Frontend: http://localhost:5173
# Backend API: http://localhost:8000
# Database Admin: http://localhost:3001
# Database API: http://localhost:8001- Docker Containers





