Realistic Coding Interviews That Hear, Watch, & Coach You
Experience an authentic technical evaluation powered by conversational AI voice. The interviewer speaks out loud, observes your keystrokes live via WebSockets, provides gentle coaching hints when you get stuck, and outputs a rigorous hiring scorecard.
“Welcome! Let's start with a coding challenge in Python. How would you group anagrams from a list of strings in O(N × K) time?”
“We can iterate through each word, sort its characters or build a character count tuple as a hash map key, and append the original word.”
“I see you started setting up the hash table. Remember that in Python, tuples are hashable and can be used directly as dictionary keys.”
from collections import defaultdict
def group_anagrams(words: list[str]) -> list[list[str]]:
anagram_map = defaultdict(list)
for word in words:
# Group by character frequency tuple
key = tuple(sorted(word))
anagram_map[key].append(word)
return list(anagram_map.values())How the AI Technical Interview Works
From voice greeting to sandbox execution and final hiring scorecard.
1. Stack & Difficulty Setup
Choose from 9 specialized language banks (JavaScript, Python, Java, C++, C, C#, SQL, HTML, CSS) and select your target seniority level (Junior, Mid, Senior).
2. Conversational Phone Call
The interviewer conducts dialogue naturally using Shunya Labs Voice AI. You speak into your microphone, with automatic silence detection for natural turn-taking.
3. Live Code & Proactive Hints
Monaco Editor streams your keystrokes over WebSockets. When you pause or struggle for >35s, the AI inspects your uncommitted buffer and speaks a targeted micro-hint.
4. Evaluation & Scorecard
Your code executes in an isolated sandbox. The FSM scores correctness, communication, and depth to generate a Hiring Decision Scorecard with radar charts and rubric audit logs.
Specialized Question Banks for 9 Stacks
Every language stack is pre-loaded with junior, mid-level, and senior challenges, theory questions, and starter code stubs.
JavaScript
.js • Monaco IDEPython
.py • Monaco IDEHTML5
.html • Monaco IDECSS3
.css • Monaco IDEJava
.java • Monaco IDEC
.c • Monaco IDEC++
.cpp • Monaco IDEC#
.cs • Monaco IDESQL
.sql • Monaco IDEReliable Infrastructure Under the Hood
Engineered with multi-model fallback resiliency, isolated compilation, and automated audio synthesis.
OpenRouter Multi-Model Fallback Chain
Automatic silent failover across Claude 3.5 Sonnet, GPT-4o, Gemini 2.5 Pro, DeepSeek, and LLaMA 3.3. If an upstream model is rate-limited, the interview proceeds without interruption.
Shunya Labs Neural Voice AI
High-fidelity audio generation using Shunya Labs Zero-TTS with the Varun voice profile and zero-indic model for natural dialogue cadence.
Deterministic FSM & Sandboxing
Finite state transitions maintain interview structure without hallucinated phases. Sandboxed compiler executions measure runtime, stderr, and memory safely.
Ready to Test Your Technical Acumen?
Launch an interview in Python, JavaScript, Java, C++, or SQL. Experience real-time spoken feedback and receive your comprehensive scorecard.