购置
Greepgram 收购日报，承诺保持管道猫开源
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2026年10月29日Deepgram 宣布表示正在收购开源 Pipecat语音agent框架背后的公司"Daily"，在旧金山的"Deepgram Speak"首发会揭幕。 Daily团队将加入Deepgram，而Pipecat将完全保持开源，并根据其现有的BSD V2许可证免费给开发者。
Deepgram 称 Pipecat和Daily的全球实时网络基础设施将与其自己的语音模型一起支撑其新的Voice Agent平台，形成它所描述的第一个完整，开放，生产级的对话语音AI平台。 该公司将Pipecat定性为世界上最受欢迎的开源语音agent框架和称 Daily的网络连接终端用户与语音agents的超低空和高可靠性。
每日联合创始人克温德拉·赫特曼·克拉姆(Kwindla Hultman Kramer 加入 Deepgram)出任开源负责人。 Kramer 称在收购公告中说：“保持管道的开放对我们决定加入Deepgram至关重要。” Deepgram CEO和联合创始人Scott Stephenson 称 Kramer和Daily Team了解如何保持现场对话可靠运作，并了解如何获取Daily 带来的专业知识与Deepgram的专长一起应对整个语音系统，并让开发者从原型到制作更快的路径。
开源承诺和管道基金会
除了在 BSD V2 许可下保持框架自由外，Deepgram 称将投资给 Pipecat 的持续开发和社区，同时保持 Pipecat 开源和供应商的中立性，因此开发者可以选择和结合不同供应商的模型，工具，网络传输和API. 这些公司还与许多为该框架作出贡献和使用的组织一道，正在建立一个独立的Pipecat基金会。
Kramer在Daily博客的另一篇文章中写道，基金会将由代表整个实时AI生态系统的指导委员会管理，他写道，Daily的客户和Pipecat生态系统没有任何变化：Deepgram将出售、支持并开发Daily的所有当前产品和服务，包括WebRTC、电话和跨平台的图书馆，Pipecat将保持供应商中立。 克拉姆还写道"Deepgram"正采用"Pipecat"作为其新的语音AI产品和服务的核心。
克拉姆写道："Pipecat"有200多集成，近400名贡献者。 他赞扬了18名工程师建立这个框架，特别感谢马克，他称自其发布以来一直推动皮佩卡特的发展，并感谢领导"每日日报"的投资者——德尼特(TenOneTen)的大卫·瓦克斯曼(David Waxman)，德克特(Avidan Ross)的阿维丹·罗斯(Auvidan Ross)，德克特(Freestyle)的珍妮·莱弗库特(Jenny Lefcourt)，拉希·格鲁姆(Lachy Groom)和罗桑(Roseanne)和德·雷纳塔(Renegade Partners)——以及董事会成员李·爱德华兹(Lee Edwardwards)和罗珊·温切克(Roseanne Wincek).
公司的共同历史
Kramer回忆说，他和尼娜创办了"每日日报"(Daily)，为实时音频和视频建设基础设施，这意味着编写优化的包路由软件，在全球数十个地点设计和部署专门的计算集群，以及编写客户端库，让开发者将实时音频和视频嵌入网络，桌面和本土移动应用程序。 Daily和Deepgram于2016年一起通过Y Confinetor，他写道，Deepgram自2019年起在"Daily"的音频视频API内部为转录提供了动力。
2023年每日开始建立实时语音agents和AI-native软件实验，克赖默写作，2024年开源了Pipecat的全部：核心管弦框架，每个平台和语言的客户端SDK,RTVI消息和事件标准，Pipecat Smart Turn本土-Audio转会检测模型，SmallWebRTC Transport，和Pipecat Flows上下文工程库。 他将Pipecat描述为最广泛使用的语音agents和多模式AI框架，说它处理诸如模型之间的切换，低纬度网络传输，模型之间的流数据，转弯检测，和中断处理等问题。
根据Deepgram的公告，Daily的基础设施是一个由75个点组成的全球网络，为AI的活命性和可靠性需求而设计。 Deepgram 称本身的语音模型和实时基础设施在为全球超过5000个组织制作的动力对话语音AI，超过65万开发者使用Deepgram处理超过20万年的音频。
实时背景标准和下一步
在"Speak"(Speak)中，Stephenson还用推出，即"实时上下文标准"(RCS)，是与"管猫"团队共同开发的开放协议。 Deepgram认为，RCS解决了当前语音AI系统中的一个漏洞：单词从一个模型传到下一个模型，而周围的音频上下文，如音调，谁在说话，以及背景中发生的事情，则沿途会丢失。 RCS定义了三种新类型的元数据：来自音频的上下文，如whisper或一个不明确的单词；语言模型应如何使用这些信号的指令；以及反应应如何声音的指南。 适配器为每个模型翻译这些信号和送出指令，因此开发者可以使用来自不同提供者的模型的同一种方法。
实时上下文标准演示寄存器将RCS描述为一个开放标准，该标准在同一文本流中承载了上下文，在格式上链中的任何模型都可以产生并读取。 其演示语音为agent为名为"北风出行"的户外齿轮店提供客户服务，将Deepgram Flux 语音转文本链起来，一个读音器，每个用户会读取感想和讽刺，PhoneLLM迷你语言模型，ElevenLabs 文本转语音，部署在Pipecat Cloud上。 Deepgram邀请开发者，模型提供者，以及团队建立语音应用程序，在自己的系统中测试RCS，分享反馈，并贡献规格。
同日晚些时候"Speak"节目中，首席产品官Ed Anuff被安排预览即将到来的Deepgram Voice Agent平台，并引入了为直播对话而建的两个新模型，扩展了语言支持，以及一个旨在提高连接可靠性并降低延迟度的全球API. 将在Anuff的主旨发言后
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Acquisitions
Deepgram Acquires Daily, Commits to Keeping Pipecat Open Source
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Deepgram announced on October 29, 2026, that it is acquiring Daily, the company behind the open-source Pipecat voice agent framework, unveiling the deal at its inaugural Deepgram Speak event in San Francisco. The Daily team will join Deepgram, and Pipecat will remain fully open source and free to developers under its existing BSD V2 license.
Deepgram said Pipecat and Daily’s global real-time network infrastructure will underpin its new Voice Agent Platform alongside its own speech models, forming what it described as the first complete, open, production-grade platform for conversational voice AI. The company characterized Pipecat as the world’s most popular open-source voice agent framework and said Daily’s network connects end users to voice agents with ultra-low latency and high reliability.
Daily co-founder Kwindla Hultman Kramer joins Deepgram as Head of Open Source. “Keeping Pipecat open was fundamental to our decision to join Deepgram,” Kramer said in the acquisition announcement. Deepgram CEO and co-founder Scott Stephenson said Kramer and the Daily team understand what it takes to keep a live conversation working reliably, and that acquiring Daily brings that expertise together with Deepgram’s to tackle the whole voice system and give developers a faster path from prototype to production.
Open-Source Commitments and the Pipecat Foundation
Beyond keeping the framework free under the BSD V2 license, Deepgram said it will invest in Pipecat’s continued development and community while keeping all of Pipecat open source and vendor neutral, so developers can choose and combine models, tools, network transport, and APIs from different providers. The companies are also establishing an independent Pipecat Foundation together with many of the organizations that have contributed to and use the framework.
In a separate post on Daily’s blog, Kramer wrote that the foundation will be managed by a steering committee representing the entire realtime AI ecosystem, including companies that compete with Deepgram. He wrote that nothing will change for Daily’s customers and the Pipecat ecosystem: Deepgram will sell, support, and develop all of Daily’s current products and services, including WebRTC, telephony, and cross-platform libraries, and Pipecat will remain vendor neutral. Kramer also wrote that Deepgram is adopting Pipecat as the core of its new voice AI products and services.
Kramer wrote that Pipecat has more than 200 integrations and almost 400 contributors. He credited 18 engineers with building the framework, giving special thanks to Mark, who he said has driven Pipecat’s development since its launch, and thanked the investors who led Daily’s rounds — David Waxman at TenOneTen, Avidan Ross at Root, Jenny Lefcourt at Freestyle, Lachy Groom, and Roseanne and Renata at Renegade Partners — along with board members Lee Edwards and Roseanne Wincek.
The Companies’ Shared History
Kramer recounted that he and Nina founded Daily to build infrastructure for realtime audio and video, which meant writing optimized packet-routing software, designing and deploying specialized compute clusters in dozens of locations globally, and writing client libraries that let developers embed realtime audio and video into web, desktop, and native mobile applications. Daily and Deepgram went through Y Combinator together in 2016, he wrote, and Deepgram has powered transcription inside Daily’s audio-video APIs since 2019.
Daily began building realtime voice agents and AI-native software experiments in 2023, Kramer wrote, and open sourced all of Pipecat in 2024: the core orchestration framework, client-side SDKs for every platform and language, the RTVI messaging and events standard, the Pipecat Smart Turn native-audio turn-detection model, SmallWebRTC transport, and the Pipecat Flows context engineering library. He described Pipecat as the most widely used voice agents and multimodal AI framework, saying it handles problems such as switching between models, low-latency network transport, streaming data between models, turn detection, and interruption handling.
According to Deepgram’s announcement, Daily’s infrastructure is a global network of 75 points of presence engineered for the latency and reliability demands of live AI. Deepgram said its own speech models and real-time infrastructure power conversational voice AI in production for more than 5,000 organizations globally, and that more than 650,000 developers have used Deepgram to process more than 200,000 years of audio.
Real-Time Context Standard and Next Steps
At Speak, Stephenson also introduced the Real-Time Context Standard (RCS), an open protocol co-developed with the Pipecat team. According to Deepgram, RCS addresses a gap in current voice AI systems: words pass from one model to the next, while the audio context around them, such as tone, who is speaking, and what is happening in the background, gets lost along the way. RCS defines three new types of metadata: context from the audio, such as a whisper or an unclear word; instructions for how a language model should use those signals; and guidance for how the response should sound. Adapters translate those signals and delivery instructions for each model, so developers can use the same approach with models from different providers.
The Real-Time Context Standard demo repository describes RCS as an open standard that carries that context in the same text stream, in formats any model in the chain can produce and read. Its demo voice agent handles customer service for an outdoor gear shop called Northwind Outfitters, chaining Deepgram Flux speech-to-text, a tone reader that reads each user turn for emotion and sarcasm, the PhoneLLM Mini language model, and ElevenLabs text-to-speech, with deployment on Pipecat Cloud. Deepgram invited developers, model providers, and teams building voice applications to test RCS in their own systems, share feedback, and contribute to the specification.
Later the same day at Speak, Chief Product Officer Ed Anuff was scheduled to preview the forthcoming Deepgram Voice Agent Platform and to introduce two new models built for live conversation, expanded language support, and a Global API designed to improve connection reliability and reduce latency. Deepgram said full technical details, demos, and availability for the day’s remaining product announcements would be published on its blog following Anuff’s keynote.
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