Sold by: Decagon AI
Deployed on AWS
Decagon is the conversational AI platform to build, optimize, and scale AI agents that deliver concierge-level customer experiences across voice, chat, email, and SMS. Leading enterprises like Hertz, Samsara and Chime use Decagon to resolve customer issues end to end - without hold queues, escalations, or copy-paste responses.
4.7
Overview
Every customer deserves a concierge. Decagon makes that possible at scale.
Decagon is the leading conversational AI platform purpose-built for customer experience. AI agents handle real customer issues across voice, chat, email, and SMS - resolving them fully, without deflection or escalation. One agent intelligence layer powers every channel.
Most AI platforms are black boxes. Changing agent behavior means filing a ticket, waiting on an engineer, and hoping the output matches what you needed. Decagon's Agent Operating Procedures (AOPs) let business teams read, understand, and update agent logic in plain language - no SDK, no vendor dependency, no sprint cycle. That transparency compounds into meaningfully lower cost of ownership over time.
Decagon offers a fully white-glove deployment model for teams that want it. The difference is that the build lives in the product, not locked inside proprietary tooling only Decagon can touch. You own it.
Decagon's testing suite spans the full agent lifecycle: simulate conversations before launch, run live A/B tests with Experiments, and monitor 100% of conversations in real time with Watchtower. Duet Autopilot closes the loop - analyzing production signals and proposing validated updates with human approval gates.
Enterprises in retail, financial services, travel, and technology go live in weeks. ClassPass reduced AI support costs by 95%. Hunter Douglas generated $1M in AI-driven revenue. Avis Budget Group, Chime, and Oura Health run on Decagon today.
Highlights
- Omnichannel AI agents, one platform. Deploy across voice, chat, email, and SMS from a single agent intelligence layer. Decagon agents maintain cross-channel memory and handle outbound as well as inbound - with ultra-low latency voice built in.
- Built to iterate, not just deploy. AOPs let business teams update agent logic in natural language without engineering support. Experiments run live A/B tests on real traffic. Watchtower monitors every conversation. Duet Autopilot self-improves agents over time with integrated validation and approval gates.
- Enterprise-grade from day one. Configurable PII redaction across chat and voice. Layered guardrails running before, during, and after every conversation. Git-backed versioning with isolated staging environments. Deployed by leading enterprises in six to seven weeks.
Details
Sold by
Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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Dimension | Description | Cost/12 months |
|---|---|---|
Platform Access | Decagon platform access. Pricing determined by private offer. | $1,000,000.00 |
Dimensions summary
This listing has one pricing dimension: Platform Access, measured in Units. Your price is set through a private offer rather than a published rate. This means you negotiate terms directly with the vendor, and pricing is customized to your deal. There are no separate tiers, instance sizes, or usage add-ons to choose from on the Marketplace. You buy access to the platform under a contract, and the private offer defines your unit quantity, commitment term, and total cost.
Top-of-mind questions for buyers
The Marketplace lists Platform Access measured in Units, with the exact meaning set through your private offer. The offer defines what each unit maps to and how many you receive. Since the platform bills by AI agents handling chat, voice, and email interactions, confirm the unit definition directly with the vendor.
Platform Access covers the conversational AI platform. You can build agents with Agent Operating Procedures in natural language, test and version workflows, and monitor performance. It supports chat, voice, and email in one layer. Pre-built integrations connect to CRMs, help desks, call centers, and knowledge bases with no custom code.
Pricing is set through a private offer, not a published rate. You negotiate directly with the vendor. The offer defines your unit quantity, commitment term, and total cost. There are no separate tiers or usage add-ons to select on the Marketplace. Contact the vendor to size units to your expected support volume.
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Software as a Service (SaaS)
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Resources
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Support
Vendor support
Support available via email for sales at sales@decagon.ai and customer support at support@decagon.ai .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Kabir S.
Efficient Support Automator, Needs Better Edge Case Handling
Reviewed on Sep 04, 2026
Review provided by G2
What do you like best about the product?
I appreciate how Decagon helps automate customer support interactions by handling common questions and troubleshooting, which reduces repetitive work for our team. I like that it routes more complex issues to human agents, which allows the support team to focus on cases needing human attention. The automation helps reduce response times significantly. Also, I find the initial setup fairly easy, with straightforward integration of basic workflows. Once configured, it's pretty straightforward to manage, providing flexibility in handling involved support requests and smooth escalation to human agents.
What do you dislike about the product?
One thing that could be improved is how Decagon handles more complex or unusual customer requests. Sometimes the responses can feel too generic, and it would be helpful to have more control over the tone, escalation rules, and how it handles edge cases before handing the conversation to a human. I'd like more control over how Decagon responds to edge cases. For example, we should be able to set different tones for different types of customers or situations, define exactly when a conversation should be escalated, and customize the information passed to the human agent. A clearer way to test these rules before putting them into production would also be helpful.
What problems is the product solving and how is that benefiting you?
I use Decagon to automate customer support, reducing repetitive work, speeding up response times, and allowing my team to focus on complex cases. It handles common questions and basic troubleshooting efficiently, routing complex issues to human agents.
Akash R.
Powerful AI and streamlining customer support
Reviewed on Sep 03, 2026
Review provided by G2
What do you like best about the product?
I really like how Decagon handles repetitive customer questions without the need for constant agent involvement. It provides quick responses, which helps our support team spend more time on complex issues that require human attention. I'm also impressed by how easy it is to scale support during busy periods. Decagon can handle multiple routine conversations at once, maintaining consistent response times without putting extra pressure on our support team. The AI agents and automated customer support workflows are incredibly valuable, as they handle common questions quickly and consistently, reducing repetitive tickets and giving me more time to focus on complex customer issues.
What do you dislike about the product?
One area that could be improved is how Decagon handles more complex or unusual customer questions. Sometimes the AI needs additional context or a human agent to step in, so better handling of edge cases and smoother handoffs would make the support workflow more efficient. I'd like to see better context handling for unusual or multi-step customer issues, so the AI can understand the full conversation before responding. It would also help to have clearer confidence indicators and smoother handoffs to a human agent when Decagon is not confident in the answer.
What problems is the product solving and how is that benefiting you?
Decagon automates customer support, managing routine inquiries with AI to provide faster responses. It reduces our team's repetitive workload, allowing us to focus on complex issues. It also scales support efficiently during busy periods, maintaining consistent response times.
Akash K.
Efficient AI-Powered Customer Support
Reviewed on Aug 26, 2026
Review provided by G2
What do you like best about the product?
I like how simple and useful Decagon feels in day-to-day customer support. It quickly handles a lot of common questions, which saves me time and reduces repetitive work. The responses feel natural and the overall experience is easy to manage. The biggest benefit for me is that Decagon makes customer support faster and more efficient without complicating the process.
What do you dislike about the product?
One thing I think Decagon could improve is the accuracy and consistency of responses in some situations. Sometimes, more complex or specific customer questions may need extra attention or human involvement. I’d also like to see more customization options so the responses can be better matched to different business needs. Overall, the platform works well, but these improvements could make it even more useful.
What problems is the product solving and how is that benefiting you?
I use Decagon for AI-powered customer support, handling repetitive questions, saving time, and making support more efficient. It automates common interactions, speeds up responses, and lets my team focus on complex issues.
Sumedha R.
AI-Driven Customer Support with Room for Improvement
Reviewed on Aug 21, 2026
Review provided by G2
What do you like best about the product?
I like how Decagon combines AI with practical customer-support workflows. It stands out for its ability to automate repetitive requests, respond quickly to customers, and handle support tasks with consistency that's hard to maintain manually. It's valuable because it goes beyond simply answering questions, automating routine support tasks and providing fast, consistent responses, which help in reducing the workload on support agents. The initial setup was fairly straightforward, and the platform was intuitive enough to get started without a lot of friction.
What do you dislike about the product?
I think Decagon should improve the balance between automation and human support. While it's effective for routine requests, more complex or unusual customer issues may still require human intervention, and making those handoffs even smoother could improve the experience.
What problems is the product solving and how is that benefiting you?
I use Decagon for AI-powered customer support automation, solving high support volume and slow response times by automating repetitive questions and routine requests, which gives customers faster answers and reduces the workload on support agents.
CA Rahul B.
Boosts Efficiency with Quick Resolutions
Reviewed on Aug 20, 2026
Review provided by G2
What do you like best about the product?
I appreciate Decagon's efficiency and quick resolutions. It really helps to streamline the resolution process for companies receiving multiple customer service requests.
What do you dislike about the product?
If I notice any problems or mistakes in company policies, I find that the resolutions provided by Decagon might not be proper and correct. Also, I find the setup quite complex.
What problems is the product solving and how is that benefiting you?
I use Decagon to handle customer service requests efficiently, solving problems faster with AI agents. It streamlines resolutions according to company policies, improving response times.