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PEAKROUND INTERVIEW COPILOT

A compact cue card that stays out of your way.

PeakRound Interview Copilot listens to the meeting audio you are authorized to process, detects completed technical questions, and returns concise assistance grounded in the source context you choose — covering the question patterns asked in interviews at Amazon, Google, Meta, Microsoft, and other leading tech companies.

Company names identify interview styles; all trademarks belong to their owners, and no affiliation or endorsement is implied.

Apple NVIDIA Stripe Airbnb

The desktop companion

PeakRound AI desktop app showing the cue card with a live answer while listening
The compact window: live transcript, the current cue card, and your Career Profile — system audio is captured locally.
PeakRound AI history panel listing detected questions and cue answers in English and Chinese
Every detected question and its cue card stays in your session history, ready to scroll back through.

THREE STEPS

From download to first cue card.

  1. Create an account and add time

    Start with 15 free minutes. Credits never expire, or choose Unlimited for an active interview month.

  2. Connect this desktop

    The app shows a one-time code; confirm it in your browser. It loads your selected Career Profile automatically.

  3. Start listening

    Work alongside Zoom, Microsoft Teams, or Google Meet. Metered time begins only after listening starts.

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SAMPLE CUE CARDS

Real cue cards, captured during live tests.

Answers below were produced by the live pipeline — system audio in, cue card out — then trimmed for the page. Questions were spoken aloud, detected automatically, and answered without any manual typing.

"Implement an LRU cache."

I'll implement an LRU cache using a hash map plus a doubly linked list to get O(1) for both get and put.

  • The hash map gives O(1) key lookup; the linked list keeps recency order.
  • On get, move the node to the head (most recently used).
  • On put over capacity, evict the tail — the least recently used item.

"设计一个秒杀系统。"

秒杀系统的核心是"高并发削峰 + 库存一致性 + 快速返回"。

  • 入口层限流与风控：网关按 IP/用户维度限流、验证码拦截无效流量。
  • 缓存预热 + 库存预扣：Redis 原子扣减，避免超卖。
  • 请求队列异步下单：削峰填谷，数据库只承接有效订单。

"How would you migrate a monolith handling 40k requests per minute to microservices with zero downtime?"

I'd migrate with a strangler pattern and keep the monolith running until each service is cut over behind the same API.

  • Decompose by bounded domains; move read paths and non-critical services first.
  • Dual-write with consistency checks before flipping each write path.
  • Keep a rollback: route traffic back to the monolith per-service if error budgets burn.

Sample answers are shortened for display. Live cue cards adapt to your Career Profile and the source context you choose.

Use PeakRound AI only where transcription and assistance are permitted. Windows content protection reduces visibility in ordinary screen-capture paths, but does not guarantee exclusion from every capture path, meeting tool, or device.