HappyRobot

We've raised $150M in Series C funding at a $1.2B valuation, led by Prysm Capital and co-led by @eurazeo.

We're expanding across supply chain, insurance, energy, telecom, and airlines - building toward Enterprise Superintelligence.

Thank you to our team, customers, and investors. We’re just getting started.

Full story in the thread below 👇

HappyRobot is now officially in Singapore! 🇸🇬

After a year of deploying AI agents with customers here, our team now has a home base to grow across Asia-Pacific. Want to join us? Careers link in the thread. 👇

Adding more tools to an agent works until the instructions for different situations start competing. Every new use case makes the prompt longer, and every change means retesting the whole thing.

With agent orchestration on HappyRobot, an orchestrator agent can triage each conversation and route it to a specialized sub-agent, each with its own prompt, tools and knowledge. When the conversation changes, it takes control back and re-triages.

A customer calls to move a delivery, then mentions their last invoice looks wrong. The orchestrator hands the reschedule to a scheduling agent, takes control back when the second request comes up, and routes the invoice question to a billing agent connected over MCP.

To the customer, it’s a single seamless conversation with an agent; behind the scenes, it’s a synchronized team of specialist agents.

That’s how the operation scales. A new use case becomes a new sub-agent, not a longer prompt. Each agent stays narrow and is tested on its own, so changing one doesn’t mean retesting the rest. Handoffs can cross channels, from voice to text, and external agents plug in over MCP.

More on agent orchestration in comments.

¡Hola, Buenos Aires! Our Argentina office is officially open. 🇦🇷

After Mexico City and São Paulo, we keep growing across Latin America, and we couldn’t be more excited to build a team here.

We’re hiring for our deployments team. Careers link in the thread. 👇🏼

An agent on a live call only knows what it knew when the call started. But operations don’t pause for the conversation to finish.

Signals close that gap. A weather service, your scheduling system, or any internal tool publishes an event once, and it reaches every live agent session that needs it, across voice and text.

A storm closes a highway, and the agent tells drivers on that route mid-call. An appointment is cancelled, and the agent offers a new slot instead of confirming the old one. A rate changes mid-negotiation, and the agent works from the new number.

Each update reaches only the conversations it affects. The agent either adjusts the answer it was about to give or holds the update until the next turn, re-running tool calls on the new information when it needs to.

Agents that work from what’s true right now, not what was true when the call started.

See how Signals work - link in comments.