Choose your mic
用于 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.
团队交付的成果
产品上线时间、每个文件节省的时间和成本。同一平台，应用场景截然不同。
法律科技公司打造白标尽证平台，快速交付 8 个月。
全球研究机构推出白标定性研究平台。
法律智能公司处理 5,100+ 小时运营商通话记录，处理速度快 95%。
医疗咨询公司将会议处理时间从 8 小时缩短至 0.3 小时。
电商制造商集中进行通话审核，降低成本 85%。
招聘公司将候选人报告生成时间从 5 小时缩短至 10 分钟。
Bring your setup. Leave with a clean transcript.
一个工作会议，而不是销售宣传。无任何约束。
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.
您可以看到它实时转录
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 可自定义和白标的仪表板 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 通话评分 和 辅导, and every transcript, field, and score is queryable from Claude, ChatGPT, and Cursor through the MCP server.
与您共同打造，从第一天起精确无误
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.
- 我们设计背景、字段和 评分 around your microphones, rooms, and call types, not a template.
- 您的历史录音和文稿为以下内容奠定了基础 知识库 before go-live, mixed mics included.
- 每条录音上的结构化数据，可通过 Claude、ChatGPT 和 Cursor 查询 MCP server.
将您的应用程序集成到 Claude、ChatGPT 和 Cursor 中。
无需终端。无需 npm。无需配置。Speak AI 的 MCP 服务器提供 任何助手 100+ 款工具 在约60秒内搜索、分析和处理您的知识库。这是您的应用程序运行的同一层，通过集成层和完整的开发者 API 连接到您堆栈中的数百个应用程序。
一个平台。不是一个模型。
通用 AI 工具将你锁定在一个模型和一个引擎。Speak AI 为每个任务、文件类型和团队选择正确的模型、语音引擎和语言，因此你的应用程序永远不会被锁定到单一供应商。
Multi-model
Claude、ChatGPT 和 Gemini。按任务选择，或使用自己的密钥。
多引擎
转录内容跨多个引擎路由，适配您的音频、口音和专业术语。
100多种语言
转录和翻译多种语言，服务全球和多语言团队。
MCP、API & 集成
100+ MCP 工具和一个集成层，连接到您已运行的数百个应用程序。
团队基于 Speak AI 构建。
来自使用 Speak AI 进行研究、转录、会议和客户工作的团队的真实反馈。
常见问题
您的第一张记分卡在咨询期间在真实录音上运行。团队推出需要几天而不是几个月，因为我们与您一起构建并使用您现有的录音进行初始化。
汇总使用量，而非按座位，没有最低交易量。试点获得全额抵免。我们根据您在电话中的确切工作流程确定定价范围。
Speak AI 处理100多种语言，包括中途切换语言的对话，并可以进行翻译。
是的。白标部署在您自己的域上运行，带有您的徽标，包括代理商转售的客户端平台，加上品牌 iOS 和 Android 应用程序。
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.
企业构建支持 BAA、自定义数据处理协议、SSO 和数据驻留选项。我们根据要求共享安全文档，并根据您的需求确定每个构建的范围。
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