--- title: 'Decagon — company profile' canonical: 'https://feeny.ai/companies/decagon' type: 'company' updated: '2026-07-02' --- # Decagon > Autonomous AI agents that resolve enterprise customer support end to end across chat, voice, email, and SMS. - **Website:** https://decagon.ai/ - **Type:** Private (Series D) - **Headquarters:** San Francisco, California, United States - **Founded:** 2023 - **Founders:** Jesse Zhang, Ashwin Sreenivas - **Valuation:** $4.5B - **Total raised:** $481M+ - **Latest round:** Series D · $250M · 2026 - **Investors:** Coatue Management, Index Ventures, Andreessen Horowitz (a16z), Accel, Bain Capital Ventures, Ribbit Capital, Forerunner, Elad Gil, ChemistryVC, Definition Capital, Starwood Capital - **Business model:** Enterprise SaaS - **Industries:** Artificial Intelligence - **Open roles:** 115 - **Profile:** https://feeny.ai/companies/decagon ## What they do Decagon builds autonomous AI agents for enterprise customer support, handling chat, voice, email, and SMS from one intelligence layer. Its agents resolve requests end to end and take real actions across a company's support stack, with workflows defined in natural language via Agent Operating Procedures so CX teams can iterate without engineering. ## Overview **The two-year-old betting AI can run the contact center, not just help it** Decagon started in 2023 with a claim most support vendors only whisper: that an AI agent can actually finish a customer's request, not hand it back to a human at the first hard turn. Founders Jesse Zhang and Ashwin Sreenivas built the whole thing around Agent Operating Procedures, workflows written in plain English so a CX team can change how an agent behaves without filing an engineering ticket. The market has rewarded that bet fast. By early 2026 Decagon had signed more than 100 enterprises, raised roughly half a billion dollars, and watched its valuation triple to $4.5 billion inside six months. The catch is the one that comes with any two-year-old carrying that price tag: it now has to grow into it. ## What They Do **One intelligence layer for chat, voice, and email** Decagon sells autonomous AI agents that handle customer support across chat, voice, email, and SMS from a single engine, so a conversation that starts in a chat window can continue on a phone call without losing the thread. The agents don't just answer questions; they take action, pulling data from a CRM, processing a refund, rebooking a reservation, all under guardrails the business controls. The pitch to buyers is deflection with dignity. Instead of a rigid decision-tree bot, Decagon frames its agents as a concierge every customer gets, and it leans hard on published outcome numbers to make the case. ## Problems **Killing the vendor ticket and the black-box bot** Decagon's core argument is that legacy support automation is broken in two ways: the bots are dumb, and changing them is slow. Most vendors ship a complex SDK and a black-box implementation, so every tweak to agent behavior becomes an engineering sprint or a support ticket to the vendor. Decagon's answer is to let non-technical CX teams author and iterate on agent logic in natural language while engineers keep control of integrations, guardrails, and versioning. The company also targets the trust gap: with tools like Watchtower and step-by-step traceability, it tries to answer the question buyers actually ask, which is why did the agent do that. ### Problems addressed - Legacy support automation requires engineering sprints or vendor tickets for every change - Black-box bots make it hard to see why an agent behaved a certain way - High support volume drives cost and headcount growth - Point solutions fragment chat, voice, and email into disconnected experiences - QA can't scale to review every customer conversation - Support data (Voice of Customer) stays buried in transcripts ## Who It's For **Enterprise CX and ops leaders with real call volume** This is not built for a startup with a shared inbox. Decagon aims at mid-market and enterprise support organizations drowning in ticket volume, the kind that run rigorous RFPs and demand SOC 2, ISO 27001, and hard integration depth before they sign. It shows up most in industries where support is high-stakes and high-volume: financial services, retail and e-commerce, media and subscriptions, travel and hospitality, and telecom. The buyer is usually a VP or director of customer experience who owns a deflection number and needs to move it without adding headcount. ### Ideal customer profiles - **CX / Support Operations leader** — High ticket volume and rising costs; Slow, engineering-gated changes to bot behavior; Hitting CSAT and resolution targets without adding headcount - **Technical / engineering team** — Retaining control over guardrails, integrations, and versioning; Integrating agents into an existing support stack without custom code; Ensuring safe, compliant, reliable agent behavior at scale - **Compliance / security buyer** — Meeting SOC 2, ISO 27001, GDPR, and PCI requirements; Handling sensitive customer data with auditability and guardrails ## Products **The agent, the channels, and the copilot that tunes them** Decagon's platform splits into three jobs it repeats everywhere: build the agent, optimize it, scale it. Agents ship across voice, chat, and email on one intelligence layer, and a growing set of tools sits on top to keep them honest, with Duet acting as the copilot that turns production failures into fixes. The newer push is Duet Autopilot, announced in 2026, which promises a self-improving agent that converts live signals into updates automatically, then stages every change for human review before it goes out. ## Business Model **Enterprise contracts, priced to the outcome** Decagon is classic enterprise SaaS with no public price list. Every deal runs through sales, and pricing is built around usage and business outcomes rather than a per-seat sticker, which is why the company leans so hard on deflection and cost-reduction metrics in its pitch. That model is also its ceiling. Third-party reviews peg annual contracts well into six figures, which puts Decagon squarely out of reach for smaller teams and keeps its whole go-to-market pointed at the enterprise. ## Competition **Omnichannel and AI-native, against incumbents and point tools** Decagon competes on two fronts at once: legacy support suites like Zendesk, Intercom, and Salesforce that are bolting AI onto older products, and a wave of newer AI-native rivals chasing the same agentic support market. Its sharpest claimed edges are structural. One engine spans chat, voice, and email instead of a separate tool per channel, and the natural-language AOP approach lets CX teams iterate without engineering, which the company positions as the opposite of the black-box implementations it competes against. ### Their edge - **Unified omnichannel engine** — Chat, voice, and email run on one intelligence layer with shared memory, rather than a separate point tool per channel. - **No-code agent iteration** — AOPs let CX teams author and change agent logic in natural language, avoiding the vendor-ticket and engineering-sprint cycle of legacy implementations. - **Transparency over black boxes** — Step-by-step traceability, simulations, versioning, and Watchtower QA target the black-box complaint that dogs competing bots. ### Where they're betting - Fully autonomous operation via Duet Autopilot - Deepening voice AI quality and latency - International expansion - Landing regulated enterprise (financial services) on security and compliance ## Proof **The deflection numbers Decagon puts on the table** Decagon backs its pitch with hard customer numbers, and it names names. Chime reports 70% chat and voice resolution, one customer saw 10x higher deflection at launch than expected with a 95% cost reduction, and Rippling logged a 32% lift in deflection. Across the board the company cites figures like 80% deflection, 3x higher CSAT, 65% lower support costs, and 10M-plus customers served. These are the company's own selected wins, so read them as a highlight reel, but the specifics and the named brands behind them are unusually concrete for this category. ## What People Say **Loved out of the box, priced for the few** The recurring praise is consistent: reviewers say Decagon works better out of the box than chatbots they had tried before, deploys in about a week, integrates cleanly with tools like Zendesk, and comes with a responsive team that ships fixes fast. The complaints cluster just as tightly. The contracts are expensive enough to rule out smaller companies, real setup still leans on technical agent-building work, and more than one reviewer flags a black-box feeling, where it's hard to see why an agent did what it did. Decagon's own observability tooling is clearly aimed at that last gripe. ## Funding **$250M in, a $4.5B valuation to grow into** Decagon closed a $250 million Series D in early 2026 led by Coatue Management and Index Ventures, tripling its valuation to $4.5 billion in under six months. That came right after a $131 million Series C in mid-2025 at a $1.5 billion mark, so the company roughly tripled its price in half a year. The cap table reads like an enterprise-AI who's who: a16z, Accel, Bain Capital Ventures, Ribbit Capital, Forerunner, and Elad Gil among them. In March 2026 the company also ran its first employee tender offer at the $4.5 billion valuation, a liquidity move usually reserved for later-stage companies. ## Team & Culture **In-office, ship-fast, and hiring hard across the US and abroad** Decagon is unapologetically an in-office company, and it wears its values on the wall: Just Get It Done, Invent What Customers Want, Winner's Mindset, and The Polymath Principle. Employees describe an eng-driven, ship-fast environment with real product ownership, the kind of place that suits people who like ambiguity and velocity over process. The hiring reflects a company sprinting to keep up with its own growth. It's recruiting across engineering, sales, product, design, and operations, concentrated in San Francisco and New York with international expansion into markets like the UK and Australia. Benefits are the standard high-growth package, with a notable addition of fertility and family-building support through Carrot. ## Compensation **Frontier-startup pay, weighted toward engineering** Decagon discloses pay ranges on most roles, and they run high. US engineering bands stretch from about $175K to $430K base, with senior individual-contributor and staff roles topping out well past $400K, and product, design, and G&A roles cluster in the $150K to $380K range. Every role adds equity on top of base, which at a company that just tripled its valuation is a real part of the story rather than a footnote. Bands are also posted in GBP, CAD, EUR, and AUD as Decagon hires internationally. ## Security & Legal **Built for the security teams that run the RFP** Decagon sells to financial-services and other security-conscious enterprises, so trust is a product feature, not an afterthought. The company operates as Decagon AI, Inc. and publishes a Trust Center plus a full subprocessor list, and its JDs point to SOC 2, ISO 27001, and GDPR as the compliance bar it engineers toward. The subprocessor list is a useful tell about the stack: it runs on Google Cloud, AWS, and Azure, routes calls through Twilio, and leans on a wide spread of model providers including OpenAI, Anthropic, Cohere, and xAI. Basis Theory handles tokenized, PCI-restricted data, which signals payment-grade handling for regulated customers. ## In the News **A year of raises, launches, and a build-vs-buy argument** The headlines through 2025 and 2026 track a company moving fast: a $131M Series C at $1.5B, then a $250M Series D that tripled its valuation to $4.5B, then a first employee tender offer at that same mark. The product news moved just as quickly, with Duet Autopilot, an experimentation and A/B testing suite, Watchtower, and Agent Versioning all shipping in the same stretch. Founder Jesse Zhang has also been making the public case that in an agentic world, AI agents are never done, reframing the classic build-versus-buy calculus around software that keeps changing after you deploy it. ### Coverage - [Decagon's $250 million commitment to the AI concierge future](https://decagon.ai/blog/series-d-announcement) — Decagon Blog (2026-01-28) - [Decagon completes first tender offer at $4.5B valuation](https://techcrunch.com/2026/03/04/decagon-completes-first-tender-offer-at-4-5b-valuation/) — TechCrunch (2026-03-04) - [Decagon raises $131M Series C at $1.5B](https://decagon.ai/blog/series-c-announcement) — Decagon Blog (2025-06-22) - [Introducing Duet Autopilot: The self-improving agent for conversational AI](https://decagon.ai/blog/autopilot) — Decagon Blog (2026-06-09) - [AI agents are never done: The new build-vs-buy calculus](https://decagon.ai/blog/the-new-build-vs-buy-calculus) — Decagon Blog (2026-02-12) - [AI Agent Startup Decagon Triples Valuation To $4.5 Billion](https://www.forbes.com/sites/alexyork/2026/02/06/ai-agent-startup-decagon-triples-valuation-to-45-billion/) — Forbes (2026-02-06) - [Why MCP alone isn't enough for reliable agent tool use](https://decagon.ai/blog/getting-the-most-out-of-mcp) — Decagon Blog (2026-04-14) ## Outlook **Growing into the price tag** Decagon has the rare combination of a real product, named enterprise logos, and a war chest, all before its third birthday. The clearest risks are the ones success created: a $4.5 billion valuation set in a frothy AI market, a crowded field of both incumbents and AI-native challengers, and pricing that locks it out of everyone below the enterprise. The strategy from here is legible. Push voice and Duet Autopilot toward genuinely autonomous operation, expand internationally, and keep converting deflection metrics into signed contracts. If the outcome numbers hold up at scale, the valuation looks early rather than rich. ## Company details - **Mission:** Empower every brand to deliver concierge customer experiences, making every customer feel like the only customer. - **Products:** Decagon Voice, Decagon Chat, Decagon Email, Duet / Duet Autopilot, Watchtower, Agent Operating Procedures (AOPs) - **Notable customers:** Chime, Avis Budget Group, Cash App, Square, Oura Health, Hunter Douglas, 1-800-FLOWERS.COM, Duolingo, Curology, Valon, Rippling, Notion, Substack, ClassPass, Hertz, Away, Faire, Noom, Mercado Libre, SimplePractice, Whop, Fourthwall, Flashfood, GlossGenius, Rituals - **Customer segments:** Enterprise, Mid-market, Financial services, Retail & e-commerce, Media & subscriptions, Travel & hospitality, Telecommunications - **Buyers / users:** VP / Director of Customer Experience, Head of Support Operations, CX / Ops leaders, Technical / engineering teams supporting CX - **Competitors:** Zendesk, Intercom, Salesforce (Agentforce), Sierra, Ada, Forethought - **What sets them apart:** Omnichannel by design: chat, voice, and email on a single intelligence layer; Natural-language Agent Operating Procedures let non-technical teams iterate without engineering; Duet copilot self-improves agents from production signals; Deep observability and traceability to counter the black-box problem; Enterprise-grade security posture built for regulated buyers - **Tech stack:** Google Cloud Platform, AWS, Azure, Twilio, OpenAI, Anthropic, Cohere, xAI, ElevenLabs, Cartesia, Soniox, Baseten, Modal Labs, Together AI, Fireworks, ClickHouse, Hex, WorkOS, Clerk, Cloudflare, Vercel, Basis Theory - **Integrations:** Salesforce, Zendesk, Intercom, Kustomer, Confluence, Contentful, Amazon Connect, RingCentral, Zendesk Sunshine, MCP (Model Context Protocol), SIP trunking, APIs / custom tools ## Open roles (115) - [Senior Commercial Counsel](https://jobs.ashbyhq.com/decagon/b95c12ed-e814-4fb9-9947-be5ed3af2214) — San Francisco, CA - [Senior Software Engineer, Cloud Infrastructure](https://jobs.ashbyhq.com/decagon/87d6c46a-365c-4d97-98ca-de7e29b6cf72) — San Francisco, CA - 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[Agent Strategy Manager](https://jobs.ashbyhq.com/decagon/ac14f2e8-950e-4668-a6ff-41f80181f006) — London, United Kingdom - [Staff Software Engineer, Agent Orchestration](https://jobs.ashbyhq.com/decagon/bb53080a-2945-4d39-9ef3-ef9a6fce6219) — New York, NY - [Agent Development Manager](https://jobs.ashbyhq.com/decagon/e0f5118b-9af7-4d37-87a8-c79c8163116a) — Toronto, Canada - [Enterprise Account Executive](https://jobs.ashbyhq.com/decagon/67c794bd-e423-44b2-8b80-d7b759994cde) — San Francisco, CA - [Marketing Operations Associate](https://jobs.ashbyhq.com/decagon/c6e70f60-9ed5-416a-8b37-bff69de9db93) — San Francisco, CA - [Engineering Manager, Agent Orchestration](https://jobs.ashbyhq.com/decagon/b295b323-3d01-4126-94c1-9fc7489ebdf0) — San Francisco, CA - [Accounting Operations and Payroll Manager](https://jobs.ashbyhq.com/decagon/684d4583-6f49-4fa5-bace-5a4a0ef86ca5) — San Francisco, CA - [Staff Software Engineer, Voice Agent](https://jobs.ashbyhq.com/decagon/2351ca53-b7fd-4835-b967-4ae2b976b5b4) — San Francisco, CA - [Enterprise Account Executive](https://jobs.ashbyhq.com/decagon/a60722ec-7a38-4d1b-a603-568f1cec92c4) — London, United Kingdom - [Deal Desk Operations & Strategy Lead](https://jobs.ashbyhq.com/decagon/76b7427f-4d3a-491a-8096-745303f46a31) — San Francisco, CA - [Agent Development Manager](https://jobs.ashbyhq.com/decagon/e973eabb-2544-4323-ba60-e443dae140e5) — San Francisco, CA - [Senior Software Engineer, Agents](https://jobs.ashbyhq.com/decagon/90c40e13-345e-4855-944e-c8f6b462a78e) — San Francisco, CA - [Founder's Office, Founder Associate](https://jobs.ashbyhq.com/decagon/c309c767-3553-42e1-81ec-73cc3b88c2ce) — San Francisco, CA - [Strategic Account Director](https://jobs.ashbyhq.com/decagon/12d4dcc2-0a5a-48ef-9c47-cc45eb9bc0dd) — London, United Kingdom - [Agent Strategy Manager](https://jobs.ashbyhq.com/decagon/ebeb6781-5357-4f70-a24b-0293a659bfac) — Remote - [Technical Recruiting Coordinator](https://jobs.ashbyhq.com/decagon/47042c55-89d7-466f-85c7-a817cc5dcb6e) — San Francisco, CA - [Strategic Account Director - East](https://jobs.ashbyhq.com/decagon/9875ed62-9d62-4485-8d47-fc897d43493b) — Remote - [Staff Software Engineer, Infrastructure](https://jobs.ashbyhq.com/decagon/3014316c-545f-43ea-a7f5-7dd909bc34ff) — San Francisco, CA - [Agent Strategy Manager](https://jobs.ashbyhq.com/decagon/7ae498c6-750d-43ab-8ad2-ab05b75684eb) — San Francisco, CA - [Director of Sales, Enterprise](https://jobs.ashbyhq.com/decagon/ca69cd40-646d-44a8-a052-6f40294b123b) — San Francisco, CA - [Engineering Manager, Agents](https://jobs.ashbyhq.com/decagon/0902f176-33a3-4233-be8a-1e22d1e8d23d) — New York, NY - [Senior Platform Engineer, Security](https://jobs.ashbyhq.com/decagon/59330f7d-3489-40c1-bff1-60e95d56b112) — San Francisco, CA - [Agent Strategy Manager](https://jobs.ashbyhq.com/decagon/f45c6d16-7a06-4a3f-ade7-c915698aba75) — Toronto, Canada - [Staff Research Engineer](https://jobs.ashbyhq.com/decagon/50051fa8-a07b-4678-ad74-7b2610fcb840) — San Francisco, CA - [Senior Agent Product Manager](https://jobs.ashbyhq.com/decagon/e31c0645-7325-43b9-9d58-0acc40904240) — New York, NY - [Agent Development Manager](https://jobs.ashbyhq.com/decagon/ee0c62b4-8e2a-4f0e-9bf4-9ff139374250) — London, United Kingdom - [Agent Strategy Manager - German Speaking](https://jobs.ashbyhq.com/decagon/e3c895d1-c215-4524-8b38-cad7209291ec) — London, United Kingdom - [Staff Research Engineer](https://jobs.ashbyhq.com/decagon/9c60e60f-9438-48c7-85af-76b8ffed9f6f) — New York, NY - [Sales Development Representative (SDR)](https://jobs.ashbyhq.com/decagon/5bf50bc3-f676-4edc-90d2-bc8154d7ee84) — San Francisco, CA - [Strategic Solutions Engineer, West](https://jobs.ashbyhq.com/decagon/78745829-74ee-41cb-836c-480ca7bf9edc) — Remote - [Partnerships, Agent Delivery Lead](https://jobs.ashbyhq.com/decagon/3f81fb0a-82c4-4e3b-9ea3-d5ebcbb28ca6) — San Francisco, CA - [Staff Software Engineer, Agent Orchestration](https://jobs.ashbyhq.com/decagon/7df0a996-5a9f-496f-9f8b-c302983765b2) — San Francisco, CA - [Senior Software Engineer, Developer Experience](https://jobs.ashbyhq.com/decagon/491d67c4-b877-4ddc-895a-496eed6777ed) — San Francisco, CA - [Senior GTM Recruiter](https://jobs.ashbyhq.com/decagon/e19bc04b-5f18-4047-b3cf-7cb47a610948) — San Francisco, CA - [Senior Solutions Engineer](https://jobs.ashbyhq.com/decagon/73ef8e9d-a6b3-4817-ab02-893c4ac72bad) — New York, NY - [Strategic Account Director, Healthcare](https://jobs.ashbyhq.com/decagon/41bdd62f-0da7-4887-8251-62061bce54df) — San Francisco, CA - [Senior Software Engineer, Agents](https://jobs.ashbyhq.com/decagon/cd95c25c-fdb7-4816-8a31-6d75e86adbe0) — New York, NY - [GTM Enablement Manager](https://jobs.ashbyhq.com/decagon/0e8a35cd-be75-436e-8407-f4e8dd2d2c59) — San Francisco, CA - [Senior Software Engineer, Agent Orchestration](https://jobs.ashbyhq.com/decagon/762ee436-6acc-4700-9927-0e73d6dc4123) — New York, NY - [Staff Technical Recruiter](https://jobs.ashbyhq.com/decagon/9efceeb7-9c23-481d-84c2-7c7fa1f59ef9) — San Francisco, CA _…and 65 more at https://feeny.ai/companies/decagon/jobs_ --- _Source: https://feeny.ai/companies/decagon · profile updated 2026-07-02_