HappyRobot

Your AI agent just transferred a call. The rep needs context. Transfer Popup Node displays caller data — IDs, addresses, conversation summary — directly in the rep's telephony system. No warm handoff to skip. No tab switching. Meet reps where they already are.

HappyRobot now supports 35+ countries for phone number purchasing — with self-service compliance bundles built in. Germany, Japan, Brazil, Australia... Submit once, reuse for unlimited numbers in that country. No more reaching out to support or manually uploading docs to Twilio

Our founding FDE @Crecker14 wrote about how the FDE role evolved, what they actually do day-to-day, and where it's heading as agentic AI reshapes enterprise ops. happyrobot.ai/blog/past-pres…

AI deployments don't fail because of models. They fail because of context. Operational complexity, legacy workflows, real-world constraints — that's what kills most enterprise AI. So we embedded engineers directly in customer operations. We call them Forward Deployed Engineers.

@lukepierceops there is product to be built around this as well - once AI is implemented it should live in a system that self-identifies bottlenecks, gaps, and operational improvements (& then implements itself)

Anthropic and OpenAI are both building PE-backed consulting arms to deploy AI inside companies. Let that sink in for a second. The two companies building the most powerful AI on earth looked at the market and said "businesses can't figure out how to use this. We need to go in and do it for them." They are literally telling you where the gap is. Companies have access to the best AI models ever built. And most of them are still running on spreadsheets, disconnected tools, and manual processes because nobody showed them how to actually implement it. That's the whole game right now. Not building better models (obviously) or shipping new features. IMPLEMENTATION. Getting AI inside real workflows. Mapping the processes, building the systems, and making it stick. I've been doing exactly this for 4 years and have worked with 80+ companies at this point. It started with automation and naturally flowed into Ai. And every single engagement starts the same way. Not with AI or automation but with a process map. Because AI alone won't fix broken operations. Companies now understand that. They have not yet seen true ROI from Ai. You have to understand how the business actually runs before you touch a single tool. Where does the data live? Where are the bottlenecks? What's manual that shouldn't be? What breaks when volume goes up? That's the work, and that's what Anthropic and OpenAI just told the entire market is worth billions. Every company is going AI-first over the next 3-5 years. The demand for people who can actually make that happen is about to be unlike anything we've seen. The labs told you where the gaps are. Now go fill them.

A collections call is a good example: the AI handles empathy and negotiation (agentic), while payment plans and legal disclosures follow exact rules (deterministic). Full breakdown here: happyrobot.ai/blog/the-agent…

Enterprise AI has a false choice problem. Rigid automation (RPA) breaks when workflows deviate. Pure agentic AI is too unpredictable for production. We built a hybrid. Agentic reasoning for conversation and context, deterministic logic for the non-negotiables: API calls, data validation, hard business rules.

The revenue was always there. It just wasn't reachable. Until now. Three use cases that turned voice AI from a cost center into a growth engine: happyrobot.ai/blog/generatin…

Most companies pitch AI as a cost play. We're seeing it generate entirely new revenue. Real results from our customers: - 65K dormant accounts reactivated → 28x ROI - 4.75x more qualified leads at 75% lower cost - 18% of inbound calls booked fully autonomously at 10% higher margins

Voice is one capability. Not a platform. The difference matters when the call ends and the work begins.

Your AI workforce shares context across every function. A support call becomes a dispatch optimization. A collections call becomes a sales opportunity. One platform. Full resolution.

The question used to be build or buy. Agentic AI changed the equation. Now you can buy a platform that gives you the power of building.

@atShruti @arrayvc @wabi what a great initiative @atShruti

If you like starting companies, donuts, & beautiful views then come to our builders hike in SF this Sunday! @arrayvc team can answer all kinds of questions on how to start a rockship from day 1. Array Ventures is first investor in @wabi @happyrobot luma.com/9pff07jp

AI workers handle the volume. Humans handle the exceptions. The enterprises that win won't have fewer people making decisions. They'll have people making better ones.

We didn't pick an easy problem. We chose work defined by complexity — high exception rates, real consequences. If AI can succeed here, it can succeed anywhere.

A human salesperson makes 50 calls a day and forgets half the details. An AI makes 50,000, remembers every syllable, and refines its approach with each call.

Wasted tokens are very common when someone builds everything from scratch. CEOs shold stop that madness. Our AI-FDE would catch that and (self)fix the workflow…. If for whatever reason this had passed the adversarial agents of the Eval phase 🤷🏼‍♂️ Chipotle needs @happyrobot

Your AI works great in the demo. Does it work with street noise, interruptions, and a frustrated customer? HappyRobot's AI workers were built for exactly this. Ready for the real world. Not just the studio.

We’re not selling custom software. We’re selling software that builds custom software.

The economics of software have inverted. The old model sold potential. You paid for the ability to maybe solve a problem. The new model sells solved problems. The risk shifts entirely from buyer to seller. Systems that actually complete work.