The voice intelligence company | MIT-alum founded. LLMs read text. We listen and understand: Try Velma 2.0.

Boston, MA
Joined August 2017
We just raised $25M in new funding led by Future Ventures (@VenturesVc), with @HyperplaneVC and @lakestarvc - bringing Modulate’s total funding to $60 million. Building the next phase of audio-native AI: more models, more developers, more of the stack that actually understands voice. Where we stand today: - Ranked #1 on Hugging Face for deepfake detection and transcription - 600M+ hours of audio analyzed - 10M+ hours analyzed every month A foundational layer of the AI stack is getting more powerful. More soon.
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One month ago today, the Modulate team came together for a Red Sox game at Fenway Park during Wavelength 2026! ⚾️ With teammates coming together from different places, including our remote team members, it was a great opportunity to spend time in person, strengthen connections, and make memories outside of work. Most of us even took the T to Fenway, making the journey part of the experience! At Modulate, building a great team goes beyond the work we do. It’s about bringing people together, building connections across the team, and making time for moments like these. A great game, even better company, and a memorable night at Fenway! ⚾️🙌
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“I’m fine.” The transcript says one thing. The voice can say something completely different. Velma by Modulate hears what speech-to-text misses: tone, emotion, hesitation and conversational context. Stop transcribing. Start truly listening. Build it into your own stack with Modulate APIs. 1,000 free credits to start.👇
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primary_verdict: “ai-vocal-music” Modulate AI Music Detection returns a clip verdict, separate AI scores for vocals and instrumentals, and per-window results every 4 seconds.
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AI agents are starting to make phone calls. What happens when a business refuses to talk to them? This Tuesday, join Modulate for a LinkedIn Live on detecting AI callers and routing humans to humans, bots to bots. Join us: bit.ly/47njIOu
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Arabic. English. Arabic again. When a conversation switches languages, Modulate Transcribe detects the language of every utterance, so each turn comes back in the language actually spoken. → 100 languages, Arabic included → Speaker labels that hold across language switches → Batch and streaming
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Clinical audiology sessions are messy 👀 Overlapping speakers. Emotional nuance flat transcripts miss. Notes that need to be instant, not "eventually." One developer needed transcription that could keep up. So they built their AI Scribe SaaS on Velma 2. The result: 👉 Live diarization 👉 Emotional context per utterance 👉 Clinical notes generated in real time Their words, not ours: ⭐ 5/5: "Accurate Transcriptions with Emotional Context at a Fantastic Price." This is what audio-native voice intelligence looks like in production 💯
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Same words. Five different meanings. “I’m fine” can be relief, exhaustion, sarcasm, or a cry for help. Your transcript can’t tell the difference. Velma can. Audio-native voice intelligence, in real time. Built for teams that need to know what was meant, not just what was said.
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Building voice agents is half the problem. Knowing what’s actually happening in those conversations is the other half. In Atlanta for VON, demoing @modulate_ai at VoiceAI LIVE! today alongside @SoundHound and others. 2:40 PM, Room C. Come say hi. I’ll be listening to how you say it.
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Last week at #SFTechWeek 🎙️ From a rooftop happy hour with VoiceRun to a hackathon with fellow builders, we spent the week connecting with the people shaping the future of voice AI. Thanks to everyone who joined us. Until next time, SF!
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I used to teach spacecraft to see. Now I teach software to listen. @modulate_ai recently raised $25M, led by Future Ventures, to build the listening layer for AI. Cosmology → JPL → voice. Here’s the path 🧵
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We're hiring. 3 roles, 1 mission: make voice a force for good online. → Backend Engineer → Staff Backend Engineer → Senior ML Engineer Somerville, MA. Full time. Hybrid.
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Most developers don't switch speech-to-text providers for a small win. They switch when one option is obviously, undeniably better 🏅 That's what happened here: ⭐ 5/5 "Outstanding Accuracy, Speed, and Value" Simple API. Clear docs. Integration that takes minutes, not days. Start building.👇
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Speech recognition = audio in, text out. That's the easy version. Our CEO and Co-founder @whuffman on why real understanding means reading accent, tone, emotion, and cadence too - not just the words. We're hiring for people who think this way. See open roles: hubs.ly/Q04xDKp90 #hiring
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