JobJump

JobJump's main job, as a coding interview helper and a general interview assistant, is to turn spoken questions into text and hand you a suggested response while the call is still going. Audio gets processed by Microsoft's Azure AI Speech service for speech-to-text, and the drafted answers come from Google's Gemini 2.5 Flash model. The panel updates as the interview moves, so you can read a starter answer and then say it in your own words rather than reciting a script. It's the feature that makes the tool useful in the moment, and it's also the one that depends most on a clear microphone signal.

When a question isn't spoken, JobJump can read it off your screen. Take a screenshot of a coding prompt, an assessment page, or a diagram, and the tool generates answer hints from the image. That covers the parts of an interview a microphone can't capture, such as LeetCode-style problems or written tests. It works after a single screenshot, so you're not juggling a separate window or app.

Every session ends with a report that records the full interview and analyzes how you answered. You can revisit it later to see where you rambled, which questions you handled well, and what to work on before the next round. For anyone doing several interviews in a week, this turns each call into something you can learn from instead of a blur you half-remember. The transcript files behind it are deleted from JobJump's servers after up to seven days.

JobJump is built to run alongside the video platforms people actually use, so you don't have to leave the call or open a second service. It lives in the browser as an extension and appears in a side panel while the meeting is open. There's no separate desktop app to install, and the same extension covers all three platforms.

JobJump aims to keep your hands off the keyboard during a call. The panel is designed so you can read suggestions and move through the session with minimal clicking, which lets you stay focused on the interviewer instead of fumbling with controls. The idea is to keep the assistant quiet and out of the way until you need it.

Because you upload your resume and set the target role, company, and job description before the call, the suggestions are built around your background rather than generic answers. That makes the output noticeably more specific than what you'd get from a blank chatbot prompt. The quality still depends on how thoroughly you fill in the setup.