AI Mock Interview
Run unlimited timed coding rounds with a synthetic interviewer that grades your code, your complexity analysis and how clearly you talk through edge cases.
Open AI Mock InterviewReal time help on coding rounds, system design, debugging and behavioral questions. InterviewOra reads your screen and the audio so you ship clean answers without leaving the interview window.

Three tools, one workflow. Drill, then deploy real-time in the round.
Run unlimited timed coding rounds with a synthetic interviewer that grades your code, your complexity analysis and how clearly you talk through edge cases.
Open AI Mock InterviewAn real-time browser copilot that reads HackerRank, CoderPad and your video call audio, then streams the optimal pattern, code and complexity in sub one second.
Where strong engineers lose offers, and what senior signal looks like instead.
You see a sliding window problem and grind through brute force for 15 minutes, then run out of clock before the optimal pass.
Name the pattern out loud in the first two minutes, state time and space, then code the optimal directly with a clean dry run.
You jump to databases and microservices before clarifying scale, read write ratio or consistency model, so the bar raiser flags you as L3.
Open with functional and non functional requirements, do back of envelope capacity math, then defend your sharding, caching and consistency tradeoffs.
STAR stories run four minutes, bury the impact and never tie back to the company value the panel is grading on.
60 second situation, 90 second action with one technical detail, 30 seconds of metric impact, mapped to Amazon LP or Googleyness.
Coding, system design and behavioral, all handled real-time by your interview copilot.
DP, graphs, sliding window, trees and tries. The right pattern surfaces the moment the prompt lands in the IDE, with clean code in your preferred language and a dry run on the example input.
Capacity math, sharding, caching layers and tradeoff framing fed in real time so you sound senior on chat, feed, search, payments or ride sharing designs.
Behavioral answers grounded in your real projects and PRs, scoped to Amazon Leadership Principles, Googleyness, Meta impact or Microsoft growth mindset.
InterviewOra parses the prompt straight from the coding platform and gives you the optimal approach, code and complexity in the same flow, no copy paste.
Eight things to lock in before you sit down for a coding loop.
Two pointers, sliding window, BFS, DFS, topological sort, union find, monotonic stack, DP on subsequences. Aim for two clean solves per pattern from memory.
Python or Java for speed, plus a backup in case the platform forces it. Rehearse the standard library: sorting, heaps, hashmaps, deques and string utilities.
Hash map vs sorted array, BFS vs Dijkstra, top k with heap vs quickselect. Be ready to defend your pick in one sentence.
Functional requirements, non functional requirements, capacity math, API, data model, components, scale, failure modes. Run it on chat, feed, ride sharing and payments.
Conflict, ambiguity, failure, leadership, ownership, impact, dealing with a junior teammate and disagree and commit. Each under 3 minutes, with a metric.
Top three bullets must match keywords from the job description. Quantify scope: users served, latency improved, dollars saved, PRs landed.
Coding mock and a system design mock, recorded. Watch yourself back at 1.5x to catch filler words, hesitation and unclear narration.
Wired headset, second monitor for notes, IDE configured for the platform language, water within reach and InterviewOra overlay tested 30 minutes before the call.
One free real interview, no credit card required.