How much does Decagon AI actually cost? A 2025 Decagon pricing breakdown

AI customer support tools all promise to cut your costs and give your team superpowers, but finding out the actual price can feel like a runaround. You see the big claims, but the cost is usually tucked away behind a “Contact Sales” form.

Decagon is a big name in the enterprise AI world, and their agents are known for handling support tickets on their own. The tech is impressive, but their custom pricing isn’t for everyone. When you’re trying to set a budget, a vague “it depends” from a vendor just doesn’t cut it.

This guide gives you a clear, no-fluff look at how Decagon pricing works. We’ll cover what you get, what you might not see coming, and explain why a quote-based model might not be the best fit for your team. For a lot of businesses, clear pricing isn’t just nice to have, it’s a must.

A look at the Decagon pricing structure

The first thing to understand about Decagon’s pricing is that it’s not your typical software subscription. Most SaaS tools charge you per person (or per “seat”). Decagon is different because they view their AI agents as independent workers, not just another tool for your human agents. That means their price is based on the work the AI actually does.

You’ll typically choose between two main pricing models based on what you want to achieve:

• Per-conversation pricing: You pay a set price for every conversation the AI agent is involved in, whether it solves the problem or not.
• Per-resolution pricing: You pay a higher set price, but only for the tickets the AI manages to solve by itself.

Decagon has mentioned that the per-conversation model is their most popular one. But here’s the bottom line: all of their pricing is custom. You won’t find a pricing page on their site. To get any numbers, you have to schedule a call with their sales team for a personalized quote.

Breaking down the two Decagon pricing models

Let’s get into the details of each model and what the trade-offs are for you.

The per-conversation Decagon pricing model

This one is pretty simple: you pay a flat fee for every interaction your AI agent handles. If it touches 10,000 conversations in a month, you’re billed for 10,000 conversations.

For Decagon, this makes billing predictable and avoids arguments over what a “resolved” ticket really is. For you, it means your costs scale directly with your support volume, which can make budgeting feel straightforward.

The catch is that you’re paying for effort, not results. You get charged even if the AI gives a simple answer, fails to fix the issue, or has to pass the ticket to a human. It can feel like paying an employee just for showing up, regardless of what they get done.

The per-resolution Decagon pricing model

With this model, you only open your wallet when the AI successfully closes a ticket without human help. The cost per resolution is higher, but it ties your spending directly to the value you’re getting.

The best part is that your goals are perfectly aligned with Decagon’s. You only pay for success, which gives them a strong incentive to build a bot that works well.

The biggest headache, though, is the ambiguity. What exactly counts as a “resolution”? If a customer gets a half-baked answer and gives up, does that count? Should a simple password reset cost the same as a complicated technical fix? This gray area can lead to billing disagreements and makes it tough to forecast your spending.

What else affects Decagon pricing?

With any custom quote, the first price you hear is just the opening offer. Several other things will likely shape the final number, and they aren’t always obvious.

• Ticket Volume: This is the biggest piece of the puzzle. Companies with huge ticket volumes have more room to negotiate lower rates. If you’re a small or mid-sized business, you might not have the same leverage to get the best price.
• Complexity of Workflows: What you need the AI to do will change the quote. Basic Q&A will be cheaper than complex tasks that need to connect to other systems, like looking up order details or processing a refund.
• Onboarding and Setup: Big enterprise tools often have setup fees. Decagon doesn’t advertise them, but it’s smart to ask about potential costs for implementation or professional services to get your AI agent trained and running.
• The “Resolution” Gray Area: It’s worth saying again, the vague definition of a “resolution” can be a hidden cost. If it’s defined loosely, you could pay for interactions that didn’t actually help the customer, bloating your bill without adding real value.

What’s the catch with Decagon pricing?

While Decagon’s approach works for some large companies, it has some real drawbacks for businesses that need to be nimble and clear on costs.

The biggest problem is the lack of transparency. Without a public pricing page, you can’t tell if the tool is even in your budget range without getting on a sales call. This is a big difference from platforms like eesel AI, which post their pricing publicly so you know what you’re getting into right away.

Decagon’s model is also built for enterprise clients. The focus on high-volume deals and custom negotiations makes it a tough fit for startups and SMBs who need a tool that can grow with them without a giant upfront commitment.

This creates another issue: there’s no clear path for growth. As your business scales, how does your price change? With custom contracts, you’re stuck renegotiating terms every time your needs change, which just adds uncertainty.

Finally, with the per-conversation model, you’re paying for incomplete work. Every time the bot tries and fails, you still get a bill. This model doesn’t focus on efficiency or quality, just activity.

A real-world example: Stamp Camp’s Decagon pricing problem

Let’s look at how this plays out for a fictional company. Meet “Stamp Camp,” an online store for stamp collectors that gets swamped with support tickets during the holidays.

First, they try Decagon’s per-resolution model. During the holiday rush, ticket volume skyrockets with tricky shipping questions, and the AI’s resolution rate plummets. Their bill becomes totally unpredictable. To top it off, they get into arguments with Decagon’s billing team over what a “resolved” ticket even is when customers just give up and leave the chat.

Tired of the guessing game, they switch to the per-conversation model. Now their costs are steady, but they feel bloated. They’re paying the same amount for simple “Where’s my order?” questions as they do for complex ones, and they still pay every single time the bot fails and escalates to a person.

In the end, neither model feels right. Stamp Camp is caught between unpredictable costs and paying for effort that doesn’t produce results. They need something more flexible, transparent, and built to scale.

A transparent Decagon pricing alternative: how eesel AI’s pricing works

This is where eesel AI comes in as an answer to opaque and rigid pricing.

First off, total transparency. eesel AI publishes its pricing plans for everyone to see. You don’t have to talk to sales just to find out if it fits your budget.

Second, no per-agent fees. This is a huge plus. Unlike most help desk software, eesel AI‘s price doesn’t go up when you hire more support agents. For growing teams, this means you can add staff without your AI bill getting bigger.

Third, predictable and value-packed tiers. eesel AI has a simple interaction-based model: one interaction is one AI reply or one AI action (like tagging a ticket). It’s easy to understand and ties directly to your usage. Each plan comes with plenty of interactions, so you’re not always worried about going over your limit.

Even the entry-level Team plan gives you unlimited agents and core features like the AI Copilot, making it accessible for businesses of any size. Powerful features like training on past tickets and AI Actions are available on the Business plan without a custom, enterprise-level negotiation.

Evaluating Decagon pricing to find a model that fits your team

Decagon has a powerful AI tool with pricing aimed at the enterprise market. But its reliance on custom quotes can create a lack of transparency, unpredictable costs, and a structure that just doesn’t work for many growing businesses.

For teams that need clarity, scalability, and control over their budget, a platform with transparent, interaction-based tiers is a much better fit. It’s important to look at solutions based not just on their features, but on a pricing model that helps you grow instead of holding you back.

If transparent pricing and powerful automation that works with the tools you already use like Zendesk and Freshdesk sounds like what you need, it’s worth taking a look at eesel AI.