Наша компания
Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. When a Fortune 500 hands its customer experience to an AI agent, it is one of the largest bets the business will make that year — and enterprises of that size do not make it on a demo. Each customer has their own requirements for how an AI agent should be evaluated, and the narratives we build have to start there and hold up long after the decision is made. Data plays a central role in almost every one of those narratives, which is why Agent Data Science exists. A deployment is evaluated by many stakeholders inside the customer's organization, including senior leaders, customer experience teams, and technical functions, each with their own criteria for success. You own how performance is defined, measured, and demonstrated against these criteria, from translating them into metrics we operationalize and deliver, to improving the ones that are key to each evaluation. You hold that from the first pre-sales evaluation through the life of the account. Our team sits within Agent Product Management and focuses mostly on our largest and most complex deployments, while supporting the data needs of Decagon customers more broadly. We are small relative to that surface area, which means the scope you own is very wide and exceptionally cross-functional. The work compounds accordingly: every metric you define on a flagship deployment becomes the default for the deals that follow, and the frameworks you build outlive any single account. Demonstrating the value of our product is everyone's responsibility, not only ours. So the primary leverage we create comes from making the rest of the organization better at it. That is what lets us stay focused on the hardest and most novel measurement problems our customers bring us, which gives this team real influence over the long-term product roadmap.