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โ† practice makes perfect!

AI-powered mock interviews with live code execution, voice mode, and real-time feedback. Train like the pros.

50K+
Interviews Conducted
94%
Offer Rate
15+
DSA Topics
<2s
Code Execution
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pick your battlefield ๐ŸŽฏ

Train for Any Company

Our AI adapts its personality, difficulty, and focus based on your target company.

๐Ÿ”

Google

Optimization & edge cases mastery

Hard algorithms
Big-O proof
System Design
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Amazon

Leadership principles + scalability

LP questions
Scalable design
Real-world impact
โšก

Meta

Product thinking at scale

Social scale
Product intuition
Data structures
๐Ÿš€

Startup

Ship fast, practical trade-offs

Pragmatic code
Full-stack
Product sense
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Google Mode Active

AI personality loaded

Active
AI Interviewer: Let's dive into your solution. What's the time complexity, and can you prove it's optimal?
everything in one place ๐Ÿ“š

Everything You Need to Get Hired

AI-Powered Interviews

GPT-4 generates company-specific questions, evaluates your code, and gives real-time feedback like a senior engineer.

Voice Interview Mode

Speak your answers aloud. Our AI listens, transcribes, and evaluates your communication in real-time.

Live Code Execution

Run C++, Java, and Python in sandboxed Docker containers. 2-second timeout. Zero setup required.

Weakness Detection

AI tracks your performance across 15 DSA topics and builds a personalized practice roadmap.

Company Mode AI

Switch between Google, Amazon, Meta, and Startup modes. The AI's personality and focus changes completely.

Progress Analytics

Skill heatmaps, score trends, and topic mastery graphs give you a 360ยฐ view of your growth.

from easy to hard ๐Ÿ“

15 DSA Topics Covered

Arrays
DP
Trees
Graphs
Sliding Window
Binary Search
Recursion
Heaps
Greedy
Backtracking
Two Pointers
Hash Maps
Docker Sandbox ยท 2s Timeout

Run Code in Seconds

Write Python, C++, or Java directly in the browser. Each execution runs in an isolated Docker container โ€” completely secure.

Isolated Docker containers
2-second time limit enforced
No network or filesystem access
64MB memory limit per run
solution.py
# Two Sum ยท O(n) solution
def two_sum(nums, target):
seen = { }
for i, num in enumerate(nums):
comp = target - num
if comp in seen:
return [seen[comp], i]
seen[num] = i
Execution: 23ms ยท Memory: 14.2MB
AI: Perfect O(n) solution! Time complexity is O(n) and space is O(n) for the hash map. Score: 96/100
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Loved by Engineers

โ€œNextUp.ai's Google mode is insanely accurate. The follow-up questions were exactly what my real interviewer asked. Got the offer in 3 weeks!โ€

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Aryan Mehta
SDE @ Google

โ€œThe weakness detection helped me realize my DP skills were terrible. 2 weeks of focused practice and I cleared all 4 Amazon rounds.โ€

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Priya Sharma
SWE @ Amazon

โ€œVoice mode is a game changer. I used to panic in interviews. Practicing with the AI voice interviewer completely cured my anxiety.โ€

R
Rahul Singh
Engineer @ Meta
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