Deepgram

Imagine voice agents that listen, think, and respond in real-time, as naturally as a human can. Today, we're making that possible with the latest addition to our voice AI platform–our unified Voice Agent API. Powered by the industry's fastest speech recognition and voice synthesis, the Voice Agent API is the quickest and easiest way to build intelligent voice agents for customer support, order taking, and more. It was built to tackle some of the toughest development challenges with ease, from noisy environments and context, to network and model latency. Watch our demo to see our drive-thru agent in action, smoothly handling interruptions and complex order taking in the noisy streets of San Francisco. TL;DR Deepgram's AI Agent API delivers: 🗣 Natural-sounding conversations in real-time. 💭 Revolutionary end-of-thought detection to gracefully navigate interruptions like never before. 🎛 Developer control to choose open source, closed source, or bring your own LLM. 📈 Low costs to scale with confidence. ✅ Flexibility to meet security and privacy needs. Try the AI agent API with this interactive demo: https://lnkd.in/g3XGc3nC Start building intelligent voice agents that wow your customers. Learn more about this latest addition to our Voice AI platform and how you can get access. https://lnkd.in/gBmDHzdn

Calling all NYC Devs & Product Builders: Join our Voice AI Workshop with Amazon Web Services (AWS) next week! Learn how to build AI voice agents that listen, understand, and respond as naturally as a human, across applications like healthcare, insurance, and banking. Walk away with: 🛣️ A roadmap for implementing Voice AI in your organization 🌟 Best practices for maximum performance and reliability 🤝 A network of Voice AI experts to tap for ideas or support Space is limited! RSVP below. https://lnkd.in/gmibhywr 📌 October 10th | 10AM-2PM ET | 7 W 34th St., New York, NY

After spending time with OpenAI’s Voice Mode in #ChatGPT, we were eager to explore the API behind it. A few weeks ago, we launched our Voice Agent API, and we’ve been curious to see how the two compare. Here’s what we found—just some early thoughts. 👇 ⚡ Latency: Both solutions performed similarly when it came to response time. Whether handling simple or complex tasks, the latency felt roughly equal at ~<1sec. 📈 Consumer vs. Enterprise OpenAI’s API: We think OpenAI’s approach is more consumer-focused, (and, hot-take) likely built by chaining together models like whisper-large-v3-turbo, gpt-4o, and their 6 TTS voices for smooth, natural interactions. (Why? High cost + use of a VAD) Deepgram’s API: Our API uses a similar chained-approach, but is designed with enterprise precision in mind, especially for structured, real-time data capture—like end-of-thought detection and accurate input processing in business environments. 🤖 Voice agent systems face a big challenge: knowing when to respond. While humans easily interpret pauses in speech, AI struggles with this.  The problem? Pauses in human speech are wildly unpredictable, varying based on the speaker, content, and environment. We handle this naturally, but AI doesn't. Most systems use Voice Activity Detection (VAD), responding after a set silence period. But this often fails in real conversations, especially when people pause to think or speak carefully. Anyone who's used these systems knows how frustrating constant interruptions can be.  A better approach is "end-of-turn detection," which uses context to determine when someone's finished speaking. This requires training models on diverse conversational data to interpret both acoustic and textual cues. 📧 Email Capture: In tasks like capturing structured data (e.g., emails), Deepgram leaned into its enterprise focus, capturing “scaling@gmail.com” with precision. OpenAI also did well but with a more conversational, flexible approach. Both can shine depending on the specific use case. #️⃣ Account number capture: Deepgram excelled in handling multi-step, multi-digit inputs—essential for enterprise workflows that require high accuracy, minimal error, and consideration for customer experience. OpenAI, while conversationally smooth, tended to interrupt when more structured inputs lacked context, highlighting where it might favor consumer-friendly use cases over more formal tasks. 💡 Takeaway: OpenAI’s API seems excellent for natural, conversational interactions—likely perfect for consumer-facing experiences. Deepgram’s API is built for reliability and precision, especially in enterprise contexts where handling structured information accurately is critical. Our end-of-turn detection, trained at scale, outperforms VAD in challenging scenarios–a significant step towards more natural voice agent interactions. We’re excited to see how you build with each! #AI #OpenAI #AIAgents #ConversationalAI

Automate appointment scheduling with AI voice agents. ⚡ Ryan Baggott breaks down how to build your own in minutes using AudioCodes and Deepgram. Check it out! 👇 #AIAgents #ConversationalAI

Since releasing Aura, we’ve heard feedback from many users building conversational AI agents about the challenges of creating an end-to-end solution with streaming speech-to-text (STT), LLM processing, and text-to-speech (TTS) output. This inspired us to develop a new Aura WebSocket Text-to-speech API to support fast input streaming, ensuring your AI agents are more responsive than ever! Aura WebSocket TTS generates speech 3X faster than ElevenLabs Turbo 2.5. The WebSocket API also delivers: ✅ Low latency: 70% time savings in LLM to TTS latency with token-by-token transmission. ✅ High-quality voices: Consistent and natural-sounding voice outputs without the hassle of managing tokens. ✅ More flexibility: Scale concurrent conversations, not blocked by individual concurrent request limit. ✅ Seamless interruption handling: Stop the TTS in real-time as soon as a human interrupts. This update aims to streamline the development process and increase productivity, so you can focus on bringing your voice agents to market faster. 🚀 Read the full announcement to learn how to get started: https://lnkd.in/g2szP3kR

Catch Scott Stephenson speaking at evaluagent®'s Contact Center Performance Summit on 16th October! From AI and CX strategy to team engagement and automation, this virtual event is covering the most pressing issues facing contact centers day. Save your spot👇 https://lnkd.in/eUA-f2Zw #evaluagentsummit2024

We're thrilled to be recognized by Unite.AI as a top text-to-speech API, powering the next generation of intuitive conversational experiences. Explore the full list! 👇 https://lnkd.in/edrjgDMC

Get a closer look at our newly released Voice Agent API next week at Enterprise Connect AI! Learn how voice agents are rapidly transforming CX–reducing operational costs, automating routine support, and freeing up human agents to focus on complex issues. Catch a live demo at our booth #7 and enter to win a pair of Bose QuietComfort Headphones! #EnterpriseConnectAI

Last week, we introduced our Voice Agent API–a unified API for building intelligent voice agents. Our team recently built an automated customer support agent to give developers a glimpse into what can be built with the API. In the demo, you will see as a phone number-based ID is spoken, the AI agent gracefully handles long pauses using next-gen end-of-speech prediction. The result? AI agent conversations that flow naturally, with product-specific context needed to deliver exceptional support. What kind of voice agent will you build? Let us know in the comments!👇 -Watch demo: https://lnkd.in/gQKbKFSA -Request access to the Voice Agent API: https://lnkd.in/gCsf7PQH

We believe autonomous voice agents are set to revolutionize how people interact with technology and transform business operations. Our new Voice Agent API combines speech recognition, voice synthesis, and LLMs, enabling developers to build AI that listens, thinks, and speaks as naturally as a human. This cutting-edge technology is poised to redefine customer service and enterprise communications, enabling seamless AI-powered interactions that mirror the flow and intelligence of human dialogue. https://lnkd.in/gwY4EkuY #AIagents #AgenticAI