ConversationPilot transcribes both sides of your call as they speak — your microphone and the meeting audio as separate streams — so every word is attributed to the right person, live.
Works on Zoom, Teams & Google Meet · Mac & Windows · 7-day free trial
Live call transcription is the foundation everything else stands on. If a copilot cannot accurately hear what was just said, and reliably tell who said it, then its objection detection, its scorecard and its coaching are all built on sand. ConversationPilot treats transcription as a real-time, two-speaker problem from the start, not an afterthought you read once the call is over.
The key design choice is dual-stream capture. ConversationPilot takes your microphone — you, the operator — and the meeting or system audio — them, the counterpart — as two separate streams rather than one mixed channel. That means it never has to guess who is speaking by analysing a single blended track; it simply knows. Transcription runs continuously on both streams using Whisper, so the running transcript is speaker-attributed from the first word, with no diarisation lag and no confusion when both people talk at once.
It runs as a discreet desktop overlay on Zoom, Microsoft Teams and Google Meet, and on phone and in-person calls too, on Mac and Windows. The overlay is hidden from screen sharing and no bot joins the meeting. Because the transcript is live and accurate, the coaching that depends on it can be fast and trustworthy — and when you hang up, the post-call report is built from a clean record rather than a half-remembered one.
Live call transcription is the continuous, real-time conversion of spoken conversation into text, as the words are being said, with each line attributed to a speaker. The emphasis is on real-time: a transcript you receive after the call is a record, but a transcript produced live is an input that the copilot can act on while the conversation is still happening.
ConversationPilot transcribes using Whisper, running continuously throughout the call rather than in a single batch at the end. As you and your counterpart speak, text appears and is tagged to the correct stream. That live transcript is what feeds objection detection, buying-signal detection, the qualification scorecard and the next-best-question engine — all of which need to know not just what was said but who said it. The accuracy of everything downstream is bounded by the accuracy of the transcript, which is why getting it right in real time matters so much.
Most transcription works from a single mixed audio channel and then tries to separate the speakers afterward — a process called diarisation that is error-prone, especially when people interrupt or talk over each other. ConversationPilot sidesteps the problem entirely by capturing two separate streams: your microphone and the meeting or system audio.
Because the two voices arrive on different streams, attribution is structural rather than inferred. The system does not have to decide whether a given sentence was you or the prospect — it already knows, because it came in on a specific stream. That is what makes the transcript reliable enough to drive live coaching, and it is also what makes the speaking analytics — talk-to-listen ratio, interruptions, question frequency — exact rather than estimated. The same architecture that powers accurate transcription powers accurate analytics, because both depend on knowing precisely who spoke.
A transcription engine that only works on one platform leaves half your conversations uncovered. ConversationPilot captures audio at the system level, so the same live transcription applies wherever the call happens. On video, it sits over Zoom, Microsoft Teams and Google Meet. On phone calls and in-person meetings, it captures the audio so the transcript is produced just the same.
This breadth comes from working off audio rather than off a single meeting platform's API. By taking your microphone and the system audio separately, ConversationPilot can transcribe a Teams demo, a dialled prospect call, or a meeting across a table with the same two-speaker accuracy. No call is left without a transcript because the platform happens to be different, since the transcription works from the sound, not the app.
ConversationPilot uses Whisper for transcription — a model chosen for its accuracy across accents, terminology and real-world call audio. Whisper runs continuously on both streams so the transcript stays current with the conversation rather than arriving in a delayed lump.
That continuous transcription is the quiet workhorse behind the whole product. The live prompts that appear in under two seconds are only possible because the transcript is already there to reason over the instant the counterpart finishes speaking — the system is never waiting to figure out what was said before it can react. And because transcription happens on two clean streams, there is no time lost untangling a mixed channel, which is part of how the in-call assist stays fast. The transcript is built once, accurately, and then reused for coaching, scoring, signal detection and the post-call report.
The transcript does not just disappear when the call ends. Because ConversationPilot has been transcribing accurately and with exact speaker attribution throughout, the post-call report is built from a clean, complete record rather than from what you managed to scribble or half-remember.
The moment you hang up, that transcript feeds an automatic report — an executive summary, key points, objections raised, buying signals, risks, recommended next actions, CRM notes and a follow-up email draft. The deeper analysis runs on a stronger model than the live prompts, so the report is thorough without ever slowing the in-call assist. The practical result is that accurate live transcription gives you two things at once: trustworthy real-time coaching during the call, and a faithful written record the moment it ends — both from the same continuously produced transcript.
Live transcription that everyone can see would defeat the point of a discreet copilot. ConversationPilot runs the transcript and the overlay where only you can see them, and the overlay is hidden from screen sharing — so even when you share your screen, the live transcript and prompts never appear in what the counterpart sees. No bot joins the meeting, so there is no extra participant and nothing that signals a tool is listening.
That said, transcription means capturing what people say, and you remain responsible for complying with applicable call-recording and consent laws in your jurisdiction. The discretion is about keeping the assist out of the counterpart's view, not about hiding the practice of recording where disclosure is required. ConversationPilot gives you an accurate, private, real-time transcript to work from; using it responsibly and lawfully is part of how you should operate it.
| Capability | ConversationPilot AI | Recorders / note-takers |
|---|---|---|
| When the transcript is available | Live, as people speak | After the call |
| Speaker attribution | Exact via separate streams | Inferred diarisation |
| Capture method | Mic + system audio | Single mixed channel |
| Drives live coaching | Yes — feeds prompts | No — review only |
| Phone & in-person calls | Transcribed too | Often video-first |
| Visible to the other side | No — overlay hidden | Bot may join |
ConversationPilot transcribes both sides of your call in real time using Whisper, running continuously throughout the conversation. It captures your microphone and the meeting audio as separate streams, so each line of the transcript is attributed to the correct speaker the moment it is spoken.
Capturing your microphone and the system audio separately means speaker attribution is structural, not guessed. The copilot already knows who spoke because the audio came in on a specific stream, so there is no error-prone diarisation. That accuracy is what lets it drive live coaching and exact speaking analytics.
ConversationPilot uses Whisper for transcription, chosen for accuracy across accents, terminology and real-world call audio. It runs continuously on both streams so the transcript stays current with the conversation rather than arriving in a delayed batch at the end.
Yes. ConversationPilot captures audio at the system level, so it transcribes video calls on Zoom, Teams and Meet as well as phone and in-person conversations. The transcription works from the sound rather than from a single platform's API, so no call type is left uncovered.
No. The transcript and overlay appear only on your screen and are hidden from screen sharing, and no bot joins the meeting. You remain responsible for complying with applicable call-recording and consent laws in your jurisdiction.
Yes. The same accurate, speaker-attributed transcript built during the call feeds the automatic post-call report — summary, objections, signals, risks, next actions, CRM notes and a follow-up email draft — so the write-up reflects what was actually said.
Real-time prompts, objection handling and qualification — while the call is happening.