What is LockedIn AI?

LockedIn AI sits in a specific product category: real-time interview assistants. Software in this category listens to a live job interview, transcribes what the interviewer says, and produces a suggested answer while the question is still hanging in the air. Candidates read it as a prompt for recall and structure under pressure, not as a script to recite.

The category now has enough entrants that naming them beats pretending they do not exist: LockedIn AI, Cluely, Final Round AI, Interview Coder, Parakeet AI, Beyz AI, and SubcueAI. The promise is close to identical across all of them. What decides which one holds up in a real interview sits in the plumbing underneath, and the rest of this page opens that up.

One caveat first. Vendors here ship quickly, and any page that hard-codes a competitor's feature list or price is wrong within a quarter. For what LockedIn AI charges and supports today, treat lockedinai.com as the source of truth. What stays stable is how the category works and how to judge any tool inside it. A direct side-by-side against SubcueAI lives on the LockedIn AI alternative page.

You want to know whether LockedIn AI is meaningfully different from the rest of the shelf or the same product with a different logo. That is the right question, and this section answers it by opening the box. Every real-time interview assistant runs the same four stages, and the differences that matter cluster in the first two.

• Audio capture. Some tools capture system audio natively at the operating system level. Others need a browser tab, an extension, or a virtual audio device. Native capture hears the interviewer directly; workarounds add setup steps and fresh ways to fail mid-call.
• Speech to text. Accuracy under accents, cross-talk, and compressed call audio decides whether the model reads the real question or a mangled one. Everything downstream inherits that error.
• Answer generation. A language model turns the transcript into a suggestion. Grounding that model in your actual resume and the job description is what separates a specific answer from a generic one.
• Display. The suggestion has to reach your eyes without reaching the interviewer's. A local overlay, a second window, and an in-browser panel each carry a different exposure profile.

LockedIn AI, SubcueAI, and every other named tool implement those four stages somehow. Read a vendor's marketing against them and vague claims turn concrete fast. Each stage is broken down further on the how it works hub.

Once the pipeline is visible, comparison stops being a feature-checklist exercise. Four things decide the experience:

• Which surfaces ship. A desktop app reaches meeting clients installed on your machine. A browser extension reaches calls that run in a tab. SubcueAI ships both: a native macOS and Windows app with dual audio capture, plus a Chromium extension whose side panel assists on tab-based calls using the meeting tab's audio only, so it never transcribes your own voice.
• Latency. A suggestion that lands after you have already started talking is noise. Every vendor markets a latency claim; the only figure that counts is the one you measure in your own test call.
• Grounding. An answer written against your resume and the job description beats a generic one, and that difference shows up in follow-up questions rather than the first answer.
• Exposure profile. Where the suggestion is drawn determines what a screen share or a recording would capture.

A backend engineer preparing for a senior role at a payments company tried two assistants in a mock call before committing. One captured the interviewer's voice from system audio and had a suggestion on screen while the question was still being asked. The other needed a virtual audio device that dropped out when she switched from her headset to laptop speakers. Setup fragility, not answer quality, decided it. A structured side-by-side of the named tools sits on the comparison page.

LockedIn AI's marketing, like most in this category, emphasizes discretion. Discretion is not invisibility, and the boundary is worth stating plainly because it applies to every tool here, SubcueAI included.

• Full screen sharing. Sharing an entire screen rather than a single window or tab puts everything on that display in front of the interviewer, overlays included.
• Screen recording. A recorded session captures what was rendered, so anything visible during the call is reviewable afterward.
• Proctored assessments. Proctoring software inspects the machine itself, including running processes and open windows. Assume exposure.
• Company-managed devices. A laptop under employer management can carry monitoring you do not control, and installing anything may not be permitted.

A vendor claiming any tool is universally undetectable is overselling. The honest framing is narrower: a local overlay is not visible to a meeting application that only receives your camera and microphone streams, and that is a real property, but it stops at the four cases above. Each scenario is worked through case by case in the detectability cluster.