Our take
Maintaineda few commits in the last 90 days- Activity
- 29
- Community
- 38
- Issues
- 21
- Pull requests
- 44
+8 stars in the last 21 days
FoloUp is a focused hiring interview app with recent maintenance activity, though its lack of releases and external service dependencies merit attention before adopting it for production hiring.
Good fit if
- Your team wants shareable AI voice interviews, question generation, response analysis, and a candidate dashboard in one app.
- You can configure and operate Clerk, Supabase, Retell AI, and OpenAI, and value the option to self-host under the MIT license.
- You are comfortable evaluating a project with a few recent commits, no releases in the past year, and contributions from several people rather than a concentrated single maintainer.
Look elsewhere if
- You need a released, versioned product or a project with a recent record of closed issues. No issues were closed in the measured recent period.
- You need to avoid external voice and AI services, or their usage costs and data handling are not suitable for your hiring process.
All health signals
| Last commit | 2026-10-17 (4 days ago) |
|---|---|
| Commits, last 90 days | 1 |
| Releases, last 12 months | 0 |
| Contributors | 8 (top contributor: 75% of commits) |
| Issues closed, last 90 days | 0 |
| Pull requests merged, last 90 days | 1 |
| Project age | 21 months |
Checked on 2026-10-22 with the GitHub API.
Overview
FoloUp is an open-source platform for companies to conduct AI-powered hiring interviews. It uses Retell AI, from Retell AI, to manage voice calls and recordings, and OpenAI to generate interview questions and analyze candidate responses. The aim is to help hiring teams run and review interviews without conducting each initial interview themselves.
Teams can generate questions from a job description, send candidates a unique interview link, and review response insights and scores in a dashboard. It is a self-hostable web app, rather than a candidate-facing interview service provided by the repository maintainers.
Key Features
- Generate tailored interview questions from job descriptions.
- Create unique links to share interviews with candidates.
- Conduct conversational voice interviews that adapt to candidate responses.
- Analyze interview responses and provide insights and scores.
- View candidate performance and overall statistics in a dashboard.
Use Cases
- A small recruiting team can send initial interview links to candidates when it needs to screen applicants asynchronously.
- A company hiring for multiple roles can generate role-specific questions from job descriptions.
- Hiring managers can review interview responses and scores in one dashboard when comparing candidates.
- A developer or organization can self-host the platform and configure its own authentication, database, voice-call, and AI services.
What you need
Detected in the repository
- Node.js (from package.json)
- A Dockerfile, so it can run in a container; a Compose file sets up the related services
- Automated checks on GitHub Actions
License in plain words
MITpermissive
- Commercial use: yes
- Modify and redistribute: yes
- You must keep: the copyright and license notice
- Share your changes: no
A summary, not legal advice: the LICENSE file is what applies.
Getting Started
Clone the repository, configure the required service credentials in .env, then install and run the app:
git clone https://github.com/FoloUp/FoloUp.git
cd FoloUp
cp .env.example .env
yarn
See the README for Clerk, Supabase, Retell AI, and OpenAI setup, then start the development server with yarn dev.
Considerations
- Local setup depends on several external services: Clerk for authentication, Supabase for data storage, Retell AI for calls and recordings, and OpenAI for question generation and response analysis. Retell AI is pay-as-you-go after its introductory credits.
- The project requires Node.js. Docker and Compose support are indicated, but the README recommends Vercel for hosting.
- The measured health data shows only a few commits recently and no releases in over a year. There were no issue closures in the measured period, so teams should assess maintenance and support expectations themselves.
- The README does not describe an automated test suite, and the supplied requirements data indicates tests are absent. Validate the interview workflow and integrations in your own environment before relying on them.
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