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Dobr.AI Interview
42:05
Let's design a parking system. Can you outline the core components?
What vehicle types should we support?
Cars, motorcycles, and buses. Each with dedicated spots.
API Design
1classParkingSystem:
2def __init__(self, num_floors):
3self.floors = []
4self.rates = {"car": 2}
5self.tickets = {}
6# Need to implement this
7
8def park_vehicle(self, vehicle):
9pass# Need to implement this
10
11classVehicle:
12def __init__(self, type, license_plate):
13self.type = type
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AC
Alex Chen
Full Stack Developer
Strong Hire
Comprehensive Skill AssessmentA spider chart showing two layers of scores against 11 skill axes. Layer 1 (Blue) scores: System Design (90%), Problem Solving (85%), Coding Proficiency (88%), Communication (78%), Tech Breadth (82%), DevOps (65%), UI/UX (70%). Scores for Machine Learning, React, LLM, Prompting are zero for Layer 1. Layer 2 (Green) scores: Machine Learning (75%), React (92%), LLM (80%), Prompting (70%), DevOps (75%), UI/UX (60%). Scores for System Design, Problem Solving, Coding Proficiency, Communication, Tech Breadth are zero for Layer 2.System DesignMachine LearningProblem SolvingReactCoding ProficiencyLLMCommunicationTech DepthPromptingBackendAWSFastAPI
Key Strengths
Component Design
API Structure
Error Handling
Clarity
Feedback Highlights:
"Your design for the parking system was well-structured with clear component separation. Consider additional scalability approaches for handling peak traffic scenarios."
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Experience a technical interview platform designed with industry standards in mind

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Real-World Skill Assessment
How It Works

Evaluate Real Skills in 3 Simple Steps

Transform your technical hiring workflow with AI-driven project assessments.

1

Define Your Assessment

Choose from expert-designed project templates (system design, coding tasks, marketing drafts) or customize assessments tailored to your specific role requirements.

  • Role-specific project templates
  • Customizable evaluation criteria
  • Supports Engineering, Product, Finance, etc.
Frontend Engineer Round
4 candidates
Alex Morgan
Senior
Scheduled
Jamie Chen
Mid-level
Completed
Taylor Wong
Senior
Pending
Sam Rivera
Junior
Scheduled
2

AI Conducts Collaborative Interview

Candidates work *with* our AI interviewer on the project, demonstrating practical skills, problem-solving, and communication in a realistic, interactive session.

  • Interactive project environment
  • Real-time collaboration simulation
  • Assesses beyond code correctness
Live Interview
In Progress
Byte

Implement a rate limiter class with a token bucket algorithm to control API request flow.

You

I'll create a RateLimiter class that refills tokens over time and checks if requests are allowed based on available tokens.

RateLimiter.js
class RateLimiter {
constructor(maxTokens, refillRate) {
this.maxTokens = maxTokens;
this.tokens = maxTokens;
this.refillRate = refillRate;
this.lastRefill = Date.now();
}
// Check if request is allowed
allowRequest() {
this._refill();
}
}
3

Get In-Depth Skill Analysis

Receive comprehensive reports detailing practical skill proficiency, communication effectiveness, and overall technical fit, going far beyond traditional pass/fail metrics.

  • Detailed skill breakdown
  • Objective, bias-free evaluation
  • Actionable hiring recommendations
Alex Morgan • Assessment Report
86/100
Recommended for hire
Top 15% of candidates
Technical Skills
92%
Problem Solving
88%
Code Quality
85%
Communication
78%
Uncompromising Integrity

Iron-Clad Anti-Cheating

In an era where AI is becoming an integral part of an engineer's toolkit, Dobr.AI redefines interview integrity. Beyond basic proctoring features, our platform focuses on assessing genuine problem-solving skills and critical thinking in a dynamic environment.

Interactive Discussions

Voice-based conversations require candidates to articulate their thought process

Real-time Adaptation

Dynamic questions that adjust based on candidate responses

Activity Monitoring

AI-powered detection of unusual patterns and plagiarism

Concept Verification

Probing questions that verify deep understanding

Interview Integrity
Advanced Protection
Interviewer

I see you've implemented the solution using a HashMap. Could you explain why you chose this data structure?

Candidate

I used a HashMap for O(1) lookup time. Since we need to access values frequently, this gives better performance than an array...

Interviewer

Great. What would be the space complexity trade-off compared to your alternative approaches?

Voice Verified
Pattern Analysis
What Sets Us Apart

Why Dobr's AI Interviews Work

Our platform delivers practical, reliable technical assessments that predict real-world performance.

Test Real-World Skills

Assess practical abilities through interactive projects (design, coding, analysis) that mirror on-the-job tasks, not just abstract algorithms.

In-Depth Skill Analysis

Get detailed reports on technical proficiency, problem-solving methods, and communication clarity with objective, standardized criteria.

Save Hundreds of Eng Hours

Automate realistic technical assessments. Schedule interviews 24/7, get instant results, and free up your senior engineers.

Truly Unbiased Evaluation

Eliminate human bias. Our AI provides consistent, data-driven assessments focused purely on technical merit and practical application.

Flexible & Scalable

Easily scale your hiring across roles (Eng, Product, Finance) with customizable project-based assessments.

Beyond Code: Assess Understanding

Our AI probes *how* candidates solve problems, verifying deep understanding and preventing cheating which is common in static tests.

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Tech Lead - RedBus

"Detailed feedback was spot-on and identified my weak areas precisely."

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SDE - Backbase

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