What is Decagon? A plain English guide to its agentic AI platform

Decagon is getting a lot of buzz in the AI customer experience (CX) world. They’re backed by some serious funding and have impressive logos like Notion, Rippling, and Bilt on their website. Their marketing promises to revolutionize customer service automation, which sounds great.

But if you’re a busy CX or operations leader, trying to cut through the polished marketing to figure out what they actually do, how the platform works, and what the potential downsides are can feel like a full-time job.

This guide is a straightforward, no-fluff look at the Decagon platform and its core “Agent Operating Procedures” (AOPs) technology. We’ll also examine their implementation process and compare their all-in-one approach to more flexible, integration-first alternatives that work with the tools your team already knows and loves.

What is agentic AI and what is Decagon?

First, a quick primer on “agentic AI.” Think of it as the next level of AI. It doesn’t just find answers; it can understand goals, reason through problems, and take multi-step actions to solve complex issues, almost like one of your best human agents.

This is the space Decagon plays in. They offer an AI platform designed to handle tricky customer service requests over chat, email, and voice. The centerpiece of their tech is something they call Agent Operating Procedures (AOPs), which they pitch as a modern upgrade to old, rigid decision trees.

Decagon’s marketing emphasizes transparency, quick deployment, and reliable results. But here’s where it gets interesting. If you dig into their own documentation, you find that getting set up requires a lot of heavy lifting from their internal team of “Agent Product Managers.” This hints that it might be less of a simple plug-and-play tool and more of a hands-on managed service.

An overview of the Decagon platform and its features

The Decagon platform is an all-in-one system with an “AI agent engine” at its core. Let’s break down the main parts.

The core concept of Decagon: Agent Operating Procedures (AOPs)

AOPs are Decagon’s special recipe for building AI logic. The idea is to mix natural language instructions (written by your business team) with code (managed by your technical team). Decagon claims this blend gives you speed, flexibility, and security.

But in practice, this “natural language + code” model means your team isn’t fully in control. Your CX team can map out the basics, but the moment you need to handle a real-world messy problem or connect to an API, you have to call in developers or Decagon’s own experts. This can easily create bottlenecks, slow you down, and shift control away from the people who actually talk to your customers.

What if your CX team could build and tweak AI workflows themselves, without needing to file a ticket with developers? With eesel AI, prompts and setups are all done in plain English, putting the power back in the hands of your support experts.

Decagon channel-specific products and agent-facing tools

Decagon offers separate products for Chat, Email, and Voice, plus internal tools like “Agent Assist” (a copilot for agents) and “Watchtower” (for QA).

The big catch here is that you can’t just pick and choose. These tools are all part of one big platform. Want to use their Agent Assist? You have to migrate your entire help desk over to their system. This “rip-and-replace” approach is a huge undertaking, forcing your team to ditch the help desk they’re used to and spend months on a painful migration.

Rather than making you rip out the tools your team knows and loves, eesel AI offers a full suite of solutions including an AI Agent, AI Copilot, and AI Triage that plug right into your current setup, whether that’s Zendesk or Freshdesk. It’s a way to get powerful AI help without the massive headache of a platform change.

Decagon Platform comparison table

The Decagon implementation model: what it really takes

Decagon’s own blog post, “What it’s like to build AI agents at Decagon,” gives us a peek behind the curtain. The main thing you learn is that Decagon has a special role called the “Agent Product Manager,” who is basically an “AI consultant” in charge of building and deploying agents for customers.

They say it themselves: “getting from idea to outcome requires iteration, context, and care,” and their product managers “partner directly with Decagon Engineering and Design to scope and build out the use case from end-to-end.”

Let’s be honest, that sounds less like a product you buy and more like a consulting project you kick off. This model usually means long timelines, high costs, and you’re always relying on the vendor to make tweaks. It can become the very “black box” system they claim to be against, leaving you wondering exactly how your AI is making decisions.

Now, let’s compare that to a more modern approach. With eesel AI, you can sign up, connect your knowledge sources, and run a test on your past support tickets in less than an hour. This unique “simulation before you scale” feature lets you see exactly how it will perform and what your ROI will be before you flip the switch. It’s a transparent, no-risk way to get started that a managed setup can’t offer.

Decagon pricing and security: reading between the lines

Now for two topics every business cares about: how much it costs and if it’s secure.

An opaque, enterprise-focused Decagon pricing model

One of the first things you’ll likely notice on Decagon’s website is something that’s missing: a pricing page. The only option is to “Get a demo.”

That’s usually a tell-tale sign of a classic enterprise sales process: think long sales cycles, custom quotes, and big annual contracts. It often means the final price is a mystery until the very end, and can hide extra costs for implementation, support, or even a certain number of “resolutions.” You’re left guessing what the real total cost will be.

We believe in being upfront. eesel AI has a clear, public pricing page. We use a fair, interaction-based model, so you only pay for what you use, not for each agent seat. This keeps your costs predictable and lets you grow your team without your bill blowing up. You can even start with a free trial to see the value firsthand.

Decagon security and trust compliance

To be clear, Decagon is a secure, enterprise-ready platform. They have a public Trust Center and are SOC 2 compliant, which are essential for any modern vendor.

But frankly, that’s table stakes these days. You should expect that from any serious vendor. eesel AI also has a robust security posture, with end-to-end encryption, strict data privacy controls (your data is never used to train other models), and optional EU data residency. This means security isn’t the real differentiator here. The focus should be on what really matters: flexibility, ease of use, and cost.

Is Decagon the right AI platform for you?

So, what’s the verdict on Decagon? It’s a powerful platform, no doubt. But it asks for a lot in return. You get an all-in-one system, but it comes with a complex, hands-on implementation, a mysterious and likely expensive price tag, and a “rip-and-replace” philosophy that disrupts your team’s workflow.

Its biggest challenge is that it’s a heavy, slow, and expensive path for modern, agile teams who want to stay in control of their tools and budgets.

For teams who want the benefits of agentic AI without the pain of a platform migration, a layered solution like eesel AI is the better path. It brings advanced automation into the help desk you already use, has clear and predictable pricing, and keeps your CX team in the driver’s seat.

Don’t replace your stack, supercharge it. See how eesel AI can transform your support workflows by booking a demo or starting a free trial today.