Speak '26 registration is officially open! 🔥
Voice AI is on the verge of its biggest milestone yet. On Oct 29, the people building it are getting together in SF to talk about what it takes to get there.
Register: https://t.co/ZBMUE2GVg4
$500 in Deepgram credits and a day spent building with voice AI? Get both when you join us at Deepgram Speak in SF on 10/29. Come for the connections, leave with everything you need to develop something new. Register here: https://t.co/ZBMUE2GVg4
"Four years is enough time to earn a full bachelor's degree. It's an entire presidential term. It's the time an athlete gets to train from one Olympic Games to the next. In other words, four years is a long time.
And in a place like Silicon Valley, where it's normal to switch companies every year or so, staying anywhere that long gets noticed. People ask about it. Recruiters ask about it. My friends definitely ask about it. "You're still at Deepgram?"
Yes, I am. So here's why I've stayed."
- Jose Nicholas Francisco, Deepgram
As voice AI models keep getting better, your stack should make it easy to keep up. Here’s @kwindla on swapping models in @pipecat_ai, and why Deepgram’s Flux TTS is “a really, really amazing step forward.” Watch the full webinar: https://t.co/bDXxPRYjDo
As AI agents get more capable, safety becomes a systems problem. What can they access, do, and decide?
Our CEO @deepgramscott joined @mishindan1 and @gsivulka on @jason’s @ThisWeeknAI to talk about guardrails and the infrastructure behind useful AI. https://t.co/G3eqGUxKLw
One month until Deepgram Speak.
On October 29th, 500 builders, researchers, and technical leaders meet in San Francisco to push voice AI forward.
Hear from teams across @BankofAmerica, @covaldev, @cresta, @LangChain, @Qualcomm, @ToastTab, @twilio, @Vapi_AI and more on what it takes to build voice AI for the real world, from latency and interruptions to multilingual agents, contact centers, and production scale.
📍 San Francisco
🗓️ October 29
🎟️ Free to attend. Only 500 seats.
Register today: https://t.co/hnXLuZp6Qi
Voice AI is growing because builders keep pushing it forward, and we believe in backing teams early.
On top of the Deepgram Startup Program, we're proud to announce that we're a launch partner in @livekit's Startup Program. Pre-Series A teams get $1,000 in Deepgram credits and it works natively through LiveKit Inference.
Ready from your first line of code and as you scale.
Can't wait to see what you build: https://t.co/aqJIMhfVeo
Deepgram is ranked #17 on RepVue's Best Venture Backed Companies to Sell For! 🏆
We're especially proud because this isn't an award you apply for. Rather, rankings come from anonymous feedback by people who actually sell here.
We're hiring AEs. 📈
https://t.co/VPtug3sKis
Some of the biggest Voice AI opportunities live in places where the cloud isn’t always an option.
That’s why Deepgram is excited to support @VAST_Data's launch of DataEnclave – bringing leading AI models into customer-controlled infrastructure while helping protect sensitive data and models in use.
Deepgram already supports self-hosted Voice AI for enterprises that need greater control over where their workloads run. With VAST DataEnclave, those teams have another path to put real-time Voice AI to work in the environments that matter most.
Because the best AI infrastructure meets enterprises where they are.
More on DataEnclave: https://t.co/YcZwVwzrP9
So look who made it to @HackMIT! 🙌🏾
I’ll be here building and talking about interesting use cases when you add voice to applications.
And @DeepgramAI brought some extra motivation: Nintendo Switch 2s and some really good cookies!
I spent a few years working on dark matter detectors, including the LUX-ZEPLIN (LZ) experiment. At the time, I definitely didn’t imagine that experience would eventually lead to a company building voice AI.
It’s exciting to see the latest result from LZ getting a new signal to chase, but the bigger thing is what work like this creates around it.
When you try to answer a really hard scientific question, you have to build new instruments, new simulations, and new ways to work with massive amounts of complex data. That work doesn’t just stay inside the original experiment. It creates capabilities that go in directions nobody expected.
That’s what happened with @DeepgramAI. We were working with waveform data in particle physics and trying to understand it. That led us to think differently about how machines could process complex signals at scale. We weren’t trying to build voice AI, but eventually that’s where the work took us.
That’s what I find cool about moments like this. The discovery matters, obviously, but so do all the things that become possible because people decided to go after a hard problem in the first place.
Congratulations to the LZ team, excited to see what comes next…
@DeepgramAI first real miss of the day: "we should go left on the pricing page" came back as a maze move. left, one square, 0.99 confidence
directional language is everywhere in office speech in a way that "jump" and "duck" (probably) are not
@DeepgramAI PIVOT! ok so single words are not great for end of turn detection, the games working, but not the best experience. lets go with a maze navigator instead
@DeepgramAI Proof of concept: Robo Jumper
To keep our little robot alive, we gotta make sure we're giving correct instructions to avoid obstacles.
The bad news for this little fella: I'm in the same room my wife is taking a meeting...
So much corporate speak to ignore.
Jev is a strong fit for voice driven interaction layers with @DeepgramAI in busy spaces.
Flux "eager" turn detection fires events before you are done talking, and jev's fixed option set goes at the question a room makes hard: "was that meant for me, or the person behind me?"
Cool demo by @syntax showing @deepgramai working with @typesafeai Jev:
Deepgram accurately transcribes (STT) the raw audio with NER (via keywords), an LLM generates notes and a summary from that transcript, then Jev then fact-checks the result rather than trusting it blindly. Jev extracts topics, tags, and chapter markers, then verifies each individual claim the LLM made to catch hallucinations.
Crazy to see how many voice driven applications possibilties there are with this technology.
Video: https://t.co/w4bK0Xailq
Source: https://t.co/0gC1GzpxLc