Direct answer
Open-source AI interview software is interview automation software whose source code can be inspected, modified, and self-hosted. Aural is open source under the MIT license, which gives teams a transparent alternative to closed interview platforms.
Interview platforms handle sensitive information: candidate answers, research transcripts, scoring criteria, and sometimes recordings. When a tool touches that much evidence, some teams want more than a product demo. They want to see how the system is built and how it can be adapted to their own environment.
Why Open Source Helps
- Transparency: Technical teams can inspect the architecture, data model, API surface, and AI integration points.
- Customization: Teams can adapt prompts, providers, workflows, UI, and deployment patterns.
- Self-hosting: Organizations can run the platform in their own environment when policy requires it.
- Extensibility: Developers can build automations on top of the REST API and public docs.
Open Source Does Not Mean No Product
Open source and SaaS are not opposites. Some teams want managed cloud hosting because it is faster. Others need self-hosting because of infrastructure, compliance, or customization. Aural supports both paths: use the hosted product or inspect and deploy the open-source codebase.
When to Care Most
Open source matters most when your team has unusual deployment requirements, wants to audit the workflow, needs to customize the AI stack, or plans to embed interviews into internal systems. If your priority is simply launching a first screening workflow today, the hosted product may be the easier starting point.
For implementation details, see Open-Source AI Interview Software.