Sfinx uses Retrieval-Augmented Generation (RAG) combined with fine-tuned LLMs to power real-time technical interviews.
We clone your top interviewers using LoRA, a lightweight fine-tuning technique, enabling the model to adopt your team's tone, logic, and evaluation style. The result is a custom AI agent that interviews exactly like your best engineers.
Each Sfinx agent is built from two parallel learning streams:
1. Interviewer Modeling - We analyze real interview transcripts, highlight decision-making patterns, and fine-tune the AI on what great interviewers look for.
2. Top Performer Profiling - Using company-provided data, we extract common traits and signals from your best hires to calibrate interview focus areas.
The system combines both to run interviews tailored to your specific hiring bar.
Sfinx evolves. After each hiring cycle, it compares its recommendations with your final decisions.
By crossing this data with feedback from engineers, it continuously refines how it scores, questions, and recommends, getting sharper with every hire.
We're currently training across multiple partner teams, growing smarter and more aligned with each deployment.