HappyRobot

Ownership doesn't stop at the edge of your role. The standard for what "done" means is high. For someone who's been waiting for that kind of environment, that's not a warning. That's the pitch. "Trains like this don't pass many times in life." We here hiring: careers.happyrobot.ai

We've come together from across the world, not just for the ambition of the problems we solve, but for the standard we hold ourselves to while solving them. You have to be prepared to work very hard. The people here are sharp. The pace doesn't let up.

"This is gonna be the best experience of your life." That's how Carlos Vereterra describes working at HappyRobot.

If you're a HappyRobot customer, you're already using HappyRobot voices that can laugh, cough, sigh, clear their throat, and speak in multiple languages. And more - working seamlessly with additional models in our voice stack, they navigate pauses, filler words, backchannels, interruptions, and background noise with ease. Human like voices for human-like experiences.

Today we're launching the HappyRobot TTS model - putting the voice in our voice stack. The HappyRobot TTS solves critical limiting factors in deploying voices into the real world like latency and pronunciation of characters and numbers that need to be clearly understood.

HappyRobot has been famous for our voice experience for a long time. You want to know our secret? We have always built for the limiting factor - solving for the incremental details that determine whether a voice, an agent, can actually have a natural conversation.

Agents are both acting on data and, with every interaction, generate memory, success metrics, and critical parameters extracted from transcripts. All new operational knowledge that couldn't exist in any other way. That generated context feeds back into every future action, beginning the flywheel where execution generates context, context improves action, and intelligence compounds.

Workflows are omni-channel, can be inbound or outbound, and are built with three foundational elements: - A prompt that guides operating procedure and behavior - AI tools like document scanning with OCR and browser agents that let agents interact with the real world - Deterministic logic like API calls and webhooks that keep execution reliable

It all starts with agents - the core of the HappyRobot platform. Agents handle coordination and communication across complex workflows and earn operational context with every interaction.

In 24 months, @HappyRobot went from a cold start to serving nine of the top ten freight brokers in the U.S. They now manage millions of interactions monthly across 80+ countries and many more verticals (telco, energy, insurance, + more) What B2B AI cos can learn from this 👇

The greatest value and leverage for an enterprise lives at the top of the pyramid of work. But systems can't start at the top. Context accumulates through execution at lower levels first - high-volume, repeatable, low hanging fruit to automate. And builds to highly contextualized work - prioritization, optimization, exception handling. Climbing the pyramid is not a feature roadmap. It's a consequence of having done the work underneath. Point solutions never get there. Each new workflow starts from zero, and the business never gets smarter. The pyramid is the entire game. Where every level unlocked makes the next one more valuable.

"the pyramid of work" - really interesting framework from the @happyrobot ceo @pablorpalafox: - at the bottom, repeatable low hanging fruit. at the top, complex + strategic decision-making - context is captured by doing work - and you gotta start at the bottom and work your way up the complexity chain - and at the top there is context inside the CEO's head that would lead to step change improvement at every layer if the agent had it this is why 1) enterprise agents will be a compounding gains market 2) the goal should be to intermediate the most important interacts that happen in a business, not own "customer support" or "sales" or whatever loved this conversation with pablo and @PaarupLuis

Forward deployed engineering has become the enterprise AI motion But how do you make sure you're building a product, not delivering services? @illscience and I talked to @pablorpalafox + @PaarupLuis on how HappyRobot has scaled to dozens of customers (and $1M + contracts) 👇

We've officially opened our New York City office! 🗽 We have a growing team of talented folks running go to market and deployments. If you're interested in being an early member of our NYC team, check out our open positions: careers.happyrobot.ai This is our sixth office, following San Francisco, Madrid, Barcelona, Chicago, and Sydney. Guess which city is coming next. 👀

Starting by building and deploying them into the real world, Where they are continuously evaluated against benchmarks. With every interaction, context is captured and fed back into the business. Teams stay connected through interfaces built for visibility and collaboration. One transparent platform, compounding knowledge across your entire business.

This is the platform to put agents to work.

The limit of AI in your enterprise isn't the model. It’s what the model knows about how you operate.

@Carles_Reina @ElevenLabs Thanks for the viz @Carles_Reina in case you want to correct the info, no Elevenlabs Agents used for this one - fully built & run on @HappyRobot