How does RChilli ensure model explainability and transparency?

RChilli improves transparency by grounding results in understandable, job-relevant factors instead of opaque signals.

Matching is based on:

• Skills alignment
• Relevant work experience
• Education relevance

The system also uses structured, job-focused logic alongside AI-driven capabilities. This makes outcomes more predictable, easier to review, and easier to explain to internal teams and clients.

In practice, this means a candidate’s result can be explained through professional fit rather than through hidden or non-job-relevant attributes.

If you need further assistance, feel free to contact the RChilli Support Team by sending an email to support@rchilli.com.