Prototype AI Interviewer — Built for Adaptive, Real Conversations
Not another chatbot. An AI that listens, adapts, and challenges candidates like a real interviewer.
Why RAG-only AI Fails at Interviews
RAG (Retrieval-Augmented Generation) is great for knowledge lookup. It’s perfect for static, factual answers. But interviews are dynamic conversations that require more.
Adaptivity
Interviews require adjusting difficulty and tone based on candidate performance.
Contextual Reasoning
Asking the right follow-up question, not a canned one, is crucial for deep assessment.
Efficiency
A good interviewer knows when to end early if it's obvious the candidate isn’t a fit.
A RAG-only interviewer is basically a fancy FAQ bot.
Our Approach: Adaptive Voice AI Interviewing
At Argmax Business, we’ve built a voice-enabled prototype that makes interviews truly intelligent.
Adjusts questions based on the candidate’s answers, depth, and confidence.
Able to conclude the interview early when a decision is clear, saving time and cost.
Remembers conversation history and builds follow-up questions in real-time.
Optimized for technical interviews like Data Science & Machine Learning.
Comparison: RAG-Only vs Adaptive AI
| Feature | RAG-Only Bot | Adaptive AI Interviewer (Our Prototype) |
|---|---|---|
| Questioning Style | Static, pre-defined responses | Dynamic, adjusts to candidate answers |
| Follow-ups | None / basic clarifications | Deep, contextual probing |
| Efficiency | Runs fixed script | Ends early if decision is clear |
| Cost | Depends heavily on LLM calls | Reduced — leverages structured action model |
| Use Case Fit | FAQs, documentation bots | Candidate assessment, technical interviews |
Prototype Highlights
Supports STT and TTS for natural conversations.
Uses belief-state updates and information gain to decide the next best question.
Reduces dependence on large LLMs by using a structured action model.
Currently optimized for Logistic Regression and Data Science interviews.
Roadmap
Our long-term goal is to build an AI that can confidently say, "Hire this person," without a human ever needing to ask a technical question.
Next Steps:
- Optimize for Latency: We are testing premium STT/TTS services to ensure real-time, fluid conversations.
- Benchmark Rigorously: The prototype's decisions will be benchmarked against those of senior human interviewers to validate accuracy.
Want to see how AI can transform interviews?
We’re looking for partners, recruiters, and data science teams to test this prototype.