Choose your mic
para audio you can trust.
Speak AI reads whatever a microphone hands it: the words, the pace, and who is speaking, on every call and meeting. The best microphone for AI transcription is the one that gets a clean signal in, and the AI takes it from there. We build it with you.
Os ganhos que times entregam.
Tempo até um produto ao vivo, horas economizadas por arquivo e dólares economizados. Mesma plataforma, aplicações muito diferentes.
Empresa de legal tech constrói uma plataforma de deposition white-label, 8 meses mais rápido.
Agência de pesquisa global lança uma plataforma de pesquisa qualitativa white-label.
Empresa de inteligência jurídica processa 5.100+ horas de chamadas de operadoras, 95% mais rápido.
Empresa de consultoria de saúde reduziu o processamento de sessão de 8 horas para 0,3.
Fabricante de e-commerce centraliza revisão de chamadas e reduz em 85%.
Empresa de recrutamento reduz o tempo de relatório de candidatos de 5 horas para 10 minutos.
Bring your setup. Leave with a clean transcript.
Uma sessão de trabalho, não um discurso de vendas. Sem obrigação.
You bring your setup
Your laptop mic, headset, conference room, or podcast rig. Whatever you record meetings and calls on today.
We check your capture chain
Mic choice, room acoustics, and platform settings, mapped against the transcription accuracy your team needs.
Você vê isso transcrito, ao vivo
Your own recording, transcribed and scored on your own criteria, with a rollout plan for the whole team.
The right mic, matched to how your team meets.
Speak AI transcribes whatever you capture with, and reads better the cleaner the input is.
Remote sales calls
A USB condenser or a good headset mic keeps discovery calls and objections legible, so scoring and coaching read the actual words, not guesses.
Contact center desks
Noise-cancelling headsets cut hold-music bleed and cross-talk, so every support call transcribes cleanly enough to QA at 100%, not a 2% sample.
Conference rooms
A ceiling or tabletop array mic beats a laptop mic across a table, so hybrid meetings transcribe every voice, not just whoever sits closest.
Depositions & intake calls
A lavalier or dedicated recorder captures depositions and client intake clearly enough for a transcript your firm can rely on in the record.
Interviews & training sessions
A shotgun or lapel mic on the interviewer keeps qualitative interviews and role-play recordings transcribable, even with a quiet or distant subject.
Field recording
A handheld recorder or phone mic close to the source outperforms a laptop across a room, so field interviews still transcribe accurately later.
A different approach to microphone choice for AI transcription.
The best microphone for AI transcription is the one that gets a clean, close signal to the software: a condenser or USB mic for a quiet room, a headset or lavalier for calls and interviews, a shotgun or handheld recorder in the field. The mic does not do the transcribing. It decides how much the AI has to work with.
Why microphone choice quietly wrecks transcripts
Most teams find out their microphone was the problem after the fact: a transcript full of guessed words, a speaker who never gets identified correctly, a call that reads like it was recorded underwater. Condenser mics pick up detail and room tone, dynamic mics reject background noise but need to be close, USB mics are the easy default for a desk, and wireless lavaliers trade a little fidelity for freedom of movement. None of that is wrong on its own. The mistake is picking one without asking what the AI on the other end needs: a clear, consistent signal with the speaker close to the capsule and the room noise low.
Reading the signal, not just the words
Speak AI treats a recording the way a careful listener would, at machine speed. Speech is transcribed in your language, with 100+ supported, and the recording itself is analyzed for the three-layer language: the words, the tone, energy, and emotion in the voice, and, where available, the visuals. A clean signal from a good microphone makes every one of those layers more reliable, and a noisier one gets routed through the engine best suited to recover it, so a rushed intake call or a mid-tier headset still comes back usable.
What to check before your next recording
- “Is the mic within 6 to 12 inches of the speaker, or is it picking up the whole room?”
- “Does the noise cancellation cut a fan or an air conditioner without eating the speaker’s voice too?”
- “Is this a portable setup, or does the mic tie the recording to one desk?”
- “Does the price reflect what one bad transcript actually costs the team in re-listening time?”
From a clean signal to a searchable record
The payoff is not a better recording. It is what happens after: transcripts your team can trust the first time, sentiment and urgency scored consistently instead of some days better than others, and painéis que você pode personalizar e marca branca that track transcription accuracy and call quality over time, so this month is measured against last month instead of a gut feeling. A global entertainment leader put its FX network meetings, mixed mics and all, through this workflow and now runs automated meeting transcription and summarization across the business.
And because the same engine scores and coaches every conversation on the same criteria, once the audio lands clean it connects straight into pontuação de chamadas e coaching, and every transcript, field, and score is queryable from Claude, ChatGPT, and Cursor through the servidor MCP.
Desenvolvido com você, preciso desde o primeiro dia.
A generic AI tool starts from zero, no matter what microphone fed it. We shape the fields, scoring, and prompts around how your team captures meetings and calls, then prime the application on your existing recordings so it reads your setup correctly from the first file. You get structured data back, not just a transcript.
- Projetamos o contexto, campos e pontuação around your microphones, rooms, and call types, not a template.
- Seus registros e transcrições históricas preparam a base de conhecimento before go-live, mixed mics included.
- Dados estruturados em cada gravação, consultáveis do Claude, ChatGPT e Cursor através do servidor MCP.
Traga suas aplicações para Claude, ChatGPT e Cursor.
Sem terminal. Sem npm. Sem configuração. O servidor MCP do Speak AI oferece qualquer assistente 100+ ferramentas para pesquisar, analisar e agir sobre sua base de conhecimento em cerca de 60 segundos. É a mesma camada em que seus aplicativos rodam, conectada aos centenas de aplicativos em sua pilha através de uma camada de integrações e uma API completa de desenvolvedor.
Uma plataforma. Não um modelo.
Uma ferramenta genérica de AI o prende a um modelo e um mecanismo. Speak AI escolhe o modelo certo, mecanismo de fala e idioma para cada tarefa, tipo de arquivo e equipe, para que suas aplicações nunca fiquem presas a um único fornecedor.
Multi-modelo
Claude, ChatGPT e Gemini. Sua escolha por tarefa, ou traga sua própria chave.
Multi-mecanismo
Transcrição roteada em múltiplos motores para seu áudio, sotaques e termos.
Mais de 100 idiomas
Transcreva e traduza para dentro e para fora, para equipes globais e multilíngues.
MCP, API & integrações
100+ ferramentas MCP e uma camada de integrações que se conecta a centenas de aplicativos que você já utiliza.
Times constroem com Speak AI.
Feedback real de equipes usando Speak AI para pesquisa, transcrição, reuniões e trabalho com clientes.
Perguntas que recebemos
Seu primeiro scorecard é executado em uma gravação real durante a consulta. O lançamento para o time leva dias, não meses, porque o construímos com você e o preparamos em suas gravações existentes.
Uso agrupado, não por assento, sem volumes mínimos. Pilotos são creditados integralmente. Escopo a precificação para seu fluxo de trabalho exato na chamada.
Speak AI suporta 100+ idiomas, incluindo conversas que mudam de idioma no meio da frase, e pode traduzir para dentro e para fora.
Sim. Implantações white-label são executadas em seu próprio domínio com seu logo, incluindo plataformas de clientes que agências revendem, além de aplicativos iOS e Android personalizados.
It is a placement guideline: keep any second microphone at least three times farther from the source as the closest mic is, so multiple mics in a room do not cancel each other out. It matters less once Speak AI is analyzing the recording, since the engine is matched to the file you hand it, but clean placement still gives it more to work with.
It depends on the recording. Speak AI routes each file across multiple speech engines and picks the one suited to the audio, language, and accent, rather than forcing every file through one model, so accuracy holds up on mixed microphones and mixed rooms.
Not exactly. Microphones capture sound; Speak AI is the layer that turns the capture, whatever hardware it came from, into a transcript with tone, sentiment, and structured fields. A better microphone gives the AI more to work with, but the accuracy comes from the transcription and analysis layer, not the hardware alone.
There is not one mic that wins every room. The closest thing is matching the mic to the setup: a headset or lavalier for calls, a room or ceiling array for conference rooms, a shotgun or handheld for the field, all feeding into a transcription engine that adapts to whichever one you used.
Enterprise builds suportam BAAs, acordos de processamento de dados personalizados, SSO e opções de residência de dados. Compartilhamos documentação de segurança sob solicitação e escopo cada build conforme seus requisitos.
From a mic swap to a transcript you trust.
Book a free consult, bring a real recording from your current setup, and watch it transcribed and scored before the meeting ends. Consults include early access to new features, an extended trial, and implementation credits.
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