Let's Talk Wise — AI Interview Coaching Platform · beiryu
Let's Talk Wise — AI Interview Coaching Platform
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An interview preparation platform pairing a web application with a Chrome extension — candidates run realistic AI-led mock interviews, get scored on content and delivery, and practise directly from the job listing they are applying to.
Let's Talk Wise helps candidates prepare for job interviews by actually putting them through one. The platform runs an AI interviewer that asks role-appropriate questions, listens to the answer, and returns structured feedback on both what was said and how it was said — the two things a candidate cannot assess about themselves in the moment.
It ships as two surfaces: a web application for full practice sessions and progress tracking, and a Chrome extension that lets a candidate start a tailored mock interview from the job listing they are looking at, at the moment their motivation is highest.
Adaptive questioning — the next question is chosen from the previous answer, so a session follows the shape of a real interview rather than reading down a fixed list
Role and industry targeting — question sets specialised by profession and seniority, so a backend engineer and an account manager do not get the same interview
Spoken interviewer — questions delivered as natural speech through AWS Polly, so the candidate practises listening and responding under time pressure rather than reading
Answer evaluation — responses assessed for relevance, structure, and persuasiveness against the question that was asked
Delivery analysis — pacing, filler words, and tone measured from the audio, which is where most interview coaching actually lives
The extension is the distribution strategy as much as a feature. It activates on job listings across major career sites, reads the role context from the page, and launches a practice session tailored to that specific posting — turning a passive browsing moment into a practice session without the candidate ever navigating to the product.
Real-time media — WebRTC for low-latency audio and video capture, so analysis happens against the live session rather than an uploaded file after the fact
Speech synthesis through AWS Polly for the interviewer voice
Extension architecture — content scripts reading listing context, a background service worker holding session state, and a shared authentication bridge with the web application
Local-first storage — IndexedDB holds practice material and session data on device, keeping recordings out of transit where they do not need to be there
Shared component layer — the web app and the extension UI draw on the same design system, so the two surfaces stay visually and behaviourally consistent
Edge-deployed API routes for the latency-sensitive parts of the loop
Interview recordings are personal data of an unusually sensitive kind — someone's worst answers, recorded. The platform treats that accordingly:
On-device processing wherever the analysis can be run locally, minimising what leaves the machine at all
Encrypted storage for sessions that do need to be retained
User-controlled retention — export and deletion available without a support request
Transparent scoring — the platform explains what it evaluated and why, rather than returning an unexplained number
This project combines a real-time media pipeline, a browser extension with its own distribution logic, and an AI evaluation loop, into a product where the technical difficulty is invisible and the value is immediate.