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Real-time AI: how SmallBird AI keeps pace with a live conversation

Two things have to happen fast for assistance to be useful mid-conversation: turning speech into text, and turning that text plus your context into a relevant suggestion. Here's how SmallBird AI does both.

1. Local speech-to-text

As the conversation happens, SmallBird AI transcribes it on your machine. Keeping this step local — rather than streaming raw audio to a remote server first — keeps the pipeline close to the conversation as it unfolds.

2. Context-aware suggestions

The live transcript is combined with the context you loaded in beforehand — your CV and the job description — so what SmallBird AI surfaces is shaped by your actual background and the actual role, not generic advice. Suggestions are generated as the conversation unfolds, not precomputed from a static question bank.

3. Stays out of the way

SmallBird AI's overlay is a separate window from your call. It's built to be quick to glance at and dismiss, and it stays invisible even if you share your screen — the interviewer or other participants only ever see the call itself.

Frequently asked questions

What makes SmallBird AI 'real-time'?

Speech-to-text transcription runs locally on your machine as the conversation happens, rather than being processed after the call. A relevant suggestion can appear while a question is still being asked.

Where does the transcription happen?

Locally, on your device. The audio pipeline stays close to home as the conversation is happening, rather than depending on a round trip to a remote server just to turn speech into text.

What decides what suggestion SmallBird AI shows?

The live transcript, combined with the context you loaded in ahead of time — your CV and the job description. Suggestions are generated as the conversation unfolds and are grounded in that context rather than being generic.

Does real-time mean instant?

It means the pipeline is built to respond while the conversation is still happening rather than after it ends. Exact latency depends on your machine and the length of what's being said, but the design goal is to keep pace with a live conversation.

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