TalVivo
Try TalVivo
AI Question Generation & Live Coding Intelligence

AI-Generated Question Papers & Containerized Coding Sandboxes.

Automatically generate non-leaked, JD-grounded assessment papers with adaptive MCQs and real-world debugging challenges evaluated live in isolated Monaco micro-VMs.

python_solution.py — High-Throughput Sandbox
● Pass: 8/8 Public & Hidden Test Cases
# Auto-Graded Container Execution: Concurrency Benchmark
def process_event_stream(events: list[dict], batch_size: int = 500) -> dict:
    aggregated = defaultdict(int)
    for event in events:
        aggregated[event['tenant_id']] += event['amount_cents']
    return dict(aggregated)

# Runtime: 84ms • Memory: 14.2MB • Isolated Subprocess: PASS
Time Complexity: O(N) Optimal
Memory Footprint: 14.2 MB Ceiled
Edge Boundary Handling: 100% Passed
AI Question Generation Engine

Adaptive, non-leaked question papers grounded in your Job Description.

Standard question banks get leaked to Discord and ChatGPT within 48 hours. TalVivo dynamically generates unique question papers for every requisition using deterministic prompt templates and role calibration.

JD & Tech Stack Grounding

Paste any job description. The AI extracts required frameworks, concurrency thresholds, and API designs to craft directly relevant challenges.

Adaptive Seniority Scaling

Calibrates difficulty between Junior, Mid, Senior, and Staff engineering tiers — testing basic data structures up to distributed Raft consensus.

Hidden Edge Case Suites

Generates public sample test cases for candidate reassurance alongside hidden boundary, memory spike, and race condition test suites.

Anti-Cheat Leak Deterrence

Parameterized variations ensure no two candidates receive identical variable names or logic paths, eliminating answer sharing.

AI Strategy Co-Pilot & Paper Builder

Design Assessment Strategy with 4 flexible creation methods.

Build custom question sets, code challenges, or reuse standard verified templates. Tailor question counts, difficulty levels, and topics before inviting candidates.

Step 1 • Design Assessment Strategy

Assessment Sections & Generation Architecture

● AI Co-Pilot Active
1. Modular Assessment Sections (Toggle On / Off)
Technical MCQs
20 – 50 Role Questions
Live Coding Sandbox
1 – 3 Isolated Challenges
Aptitude & Logic
10 – 30 Reasoning Qs
2. Select From 4 Question Creation Methods

AI Generate

Provide topic suggestions, difficulty, and stack constraints to dynamically generate fresh questions.

Upload PDF

Upload your existing internal technical exam papers. The parser extracts questions, code snippets, and options.

Link Webpage

Paste any URL (blog post, documentation, or problem description) to instantly convert the content into an assessment.

Saved Assessments

Reuse benchmarked papers across hiring seasons and campus placement drives with standardized difficulty scoring.

Review & Publish
AI Agentic Intern Set A • 30 Questions (28 MCQs + 2 Coding Sandboxes)
Mixed Difficulty • ⏱️ Estimated Duration: 45 mins
Ready for Candidate Invites
Multi-Format Testing

Assessments tailored to modern developer workflows.

Practical Debugging Sandboxes

Candidates fix broken microservices, diagnose memory leaks, and refactor legacy codebases in authentic container environments.

System Design & MCQ Sets

Test architecture fundamentals, concurrency trade-offs, state management, and situational engineering judgment.

Multimodal Anti-Cheating

Integrated browser tab monitoring, clipboard tracking, and lightweight presence verification ensure total score integrity.

Connected Hiring OS Pipeline

Where this fits in the candidate journey

Next Stage: Kyra Voice AI Interviews
Recommended Next Step: Candidates who pass the coding sandbox automatically progress to a two-way conversational voice interview where Kyra evaluates their code and system design decisions.Continue →
Assessment FAQ

Frequently Asked Questions

Evaluate engineering talent on real code execution.

Build coding sandboxes and MCQ skill assessments in under 2 minutes.