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, Chime, Oura Health, 1-800-FLOWERS.COM, 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.
External link for Decagon
100 1st St
San Francisco, California 94105, US
61 W 23rd St
New York, NY 10010, US
50 York Way
London, England N7 9QF, GB
Our interns have been booked and busy this summer (both inside and outside the office). So far, that’s included an escape room, a Giants game, rock climbing, lunch and learns, and an AMA with our CEO, Jesse Zhang. And there's plenty more to come. ☀️
Excited to announce that Decagon is now available on the Amazon Web Services (AWS) Marketplace. Enterprises can now purchase Decagon directly through AWS Marketplace, making it even easier to deploy AI agents that deliver concierge customer experiences. For AWS customers, that means: 🔹 Apply existing AWS committed spend toward Decagon 🔹 Streamline procurement through AWS Marketplace 🔹 Deploy AI agents quickly on top of your existing AWS infrastructure 🔹 Bring AI to Amazon Connect without changing your existing contact center infrastructure We're proud to build with AWS and help more enterprises bring AI into production faster. Read more on our partnership below.
Open source is growing quickly, so why is its share of enterprise AI spend shrinking? On TITV with The Information, our co-founder and CEO Jesse Zhang explains why both trends can be true at the same time. As AI moves from experimentation to large scale deployment, the model choice changes. Open source excels when teams have well defined, high volume production workflows. Closed source still plays an important role for earlier stage and less structured use cases. Thanks to Akash Pasricha for having us on TITV’s one year anniversary episode! Watch the full clip below.
We're hiring Field Engineers in SF and NYC. This is one of the most cross functional technical roles at Decagon, involving everything from writing production code to directly partnering with customers. You'll work closely with our sales, engineering, and product teams, helping shape both customer outcomes and the product itself. We’re growing this team quickly and looking for people who love solving complex technical challenges and thrive in fast-paced environments. Apply in the comments below!
Decagon reposted this
Everyone assumes falling token prices mean falling AI bills, but the opposite is actually happening. I wrote down some thoughts on what explains the disconnect.
A full house for The Odyssey last night. 🍿 We teamed up with Baseten to host an early screening with customers, builders, and friends in the AI community. Thanks to everyone who joined us! What movie should we screen next?
This summer, we opened our Sydney office, and our recent roadshow across Australia with enterprise leaders across banking, retail, energy, and technology made one thing clear: Australia is moving quickly on AI. The conversation has already shifted beyond experimentation. Teams are focused on how to deploy AI agents with the right governance, visibility, and business ownership while delivering measurable outcomes for customers. We're excited to continue investing in the region and grow alongside the incredible momentum we're seeing across Australia. 🇦🇺
Meet Sebastian Chiu, an Agent Data Scientist and ultrarunner at Decagon. In episode 3 of Side Quests, we dove deep into Sebastian’s love of running. He recently ran more than 220 miles from New York City to Boston, and regularly takes on races that span more than 100 miles. We sat down to talk about what keeps him coming back to endurance running and the mindset behind taking on challenges that most people would never attempt. If you're looking for your next main quest, we're hiring! Roles are linked in the comments. 👇
Open source versus closed models has become one of the biggest debates in AI, but we think the more interesting question is when each makes the most sense. As our co-founder and CEO Jesse Zhang shared in a recent essay, frontier models are often the right choice when a use case is new. As applications mature, many workloads become better served by smaller, specialized models that can be post trained on production data and optimized for a specific task, which is the approach we’ve taken at Decagon. Thanks to Brad Gerstner and David O. Sacks for the shoutout and for diving into this topic on the All-In Podcast this weekend! Read Jesse’s full essay below.