If you're looking into AI for your customer support team, you've probably noticed two names popping up again and again: Decagon and Forethought. They’re both backed by serious funding and used by big-name companies, so they naturally end up on most shortlists for teams looking to automate their support.
But trying to figure out the real difference between them can be tough. On the surface, they seem to do similar things.
This article is here to clear things up. We’ll give you a straightforward, practical comparison of Decagon vs Forethought, looking at what they actually do, how you get them set up, and what they might cost you. While both tools are impressive, they’re built for a very specific, enterprise-heavy approach. And for a lot of teams, that’s just not the right fit.
What is Decagon?
A screenshot of the Decagon landing page, a key consideration in the Decagon vs Forethought comparison.Think of Decagon as the AI specialist. It’s designed to handle those really tricky, multi-step customer issues that require more than just a simple FAQ answer. Companies like Eventbrite and Rippling use it to build AI agents that can do things a human agent would, like processing a refund or changing an order.
Its main calling card is that its responses are 100% generative, meaning it doesn't just pull from a list of pre-written replies. It thinks on its feet and creates a unique answer for every situation. Getting this right means plugging it into your internal tools and APIs, so it can take real action. Decagon is a powerful tool for companies that want an AI to mimic their best human agent, but it often needs some engineering muscle to get there.
What is Forethought?
A screenshot of the Forethought landing page, an important factor in the Decagon vs Forethought evaluation.Forethought is the more seasoned player on the block, offering a whole suite of tools to cover the entire support journey. It's already handling a massive volume of customer chats for brands like Upwork and Lime, so it has a long track record.
Instead of one single agent, Forethought gives you a few different tools. "Solve" is for full automation, "Triage" helps route tickets to the right person, and "Assist" acts as a helper for your human agents. One of its biggest draws is a no-code tool called Autoflows, which lets your team build out automated workflows without having to call in the developers. It also helps you find and fix gaps in your knowledge base, making it a pretty complete package for big support operations.
Decagon vs Forethought: A head-to-head comparison
Okay, so both platforms want to automate your support, but they go about it in different ways. Let’s put them side-by-side to see how they really stack up.
Core features and capabilities
Decagon is all about building a single, powerful AI agent that can handle complex problems from start to finish. The goal is to create a bot that can reason its way through complicated requests, which usually means your engineering team will be involved in the setup.
Forethought, on the other hand, gives you a broader set of tools. Its no-code builder makes it easier for non-technical folks to create their own automations, and its tools for helping human agents are useful even if you’re not ready for full automation. The trade-off is that it might not be as laser-focused on the super-custom, intricate tasks that Decagon is built for.
Here’s a quick breakdown:
| Feature | Decagon | Forethought | A more agile alternative |
|---|---|---|---|
| Primary Focus | End-to-end generative AI agents for complex tasks | Multi-agent platform (automation, triage, assist) | Fast, self-serve AI for immediate results |
| Workflow Creation | Often requires engineering support | No-code AI Agent Builder (Autoflows) | Intuitive prompt editor & workflow engine |
| Agent Assist | Basic auto-reply and summarization | Full AI copilot with step-by-step guidance | AI Copilot drafts replies from past tickets |
| Knowledge Sources | Helpdesks, internal APIs | Helpdesks, knowledge bases | Helpdesks, Confluence, GDocs, Slack & 100+ sources |
| Setup Model | Sales-led, high-touch implementation | Demo required, enterprise sales process | Self-serve, go live in minutes |
Implementation and ease of use
This is where the difference really starts to show. Both Decagon and Forethought are classic enterprise platforms. You know the drill: you schedule a demo, talk to a sales rep, and then go through a guided setup process that’s managed by their team.
While that hands-on approach can be helpful, it also means you’re looking at weeks, or even months, before the tool is actually up and running. For teams that need to move quickly and show results, that kind of "heavy lift" can be a real problem.
This is where a tool like eesel AI takes a completely different path. It's built from the ground up to be self-serve. You can connect your helpdesk, set up your AI agent, and go live in a few minutes, all by yourself. It’s a faster, more modern way to get started with AI automation without the long wait.
A flowchart outlining the quick, self-serve implementation of eesel AI, a key difference when considering Decagon vs Forethought.Control, safety, and testing
Let's talk about the big fear with AI: what if it goes rogue? The last thing you want is your bot giving out wrong information or, as one person on Reddit joked, promising a customer a free Ferrari. It's a legitimate worry.
Both Decagon and Forethought have safety measures built in, but configuring them can be tricky. And you often don't know for sure how the AI will act in the wild until it's already talking to your customers.
That uncertainty is why eesel AI's simulation mode is so useful. Before your AI agent sends a single reply, you can test it on thousands of your past tickets in a safe environment. You get to see exactly how it would have responded, get solid predictions on your resolution rates, and spot any gaps in your knowledge base. It’s a risk-free way to get everything just right and build total confidence before you hit the "on" switch.
The eesel AI simulation feature provides a safe testing environment, a critical aspect of the Decagon vs Forethought debate.Decagon vs Forethought pricing: The enterprise black box
If you head over to the Decagon or Forethought websites to look for pricing, you'll come up empty. It’s a common tactic in enterprise software, and it usually signals a few things:
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The costs are high and custom. Prices are tailored to your company and often start in the tens of thousands of dollars per year.
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You'll be signing a long-term contract. Get ready for an annual or multi-year commitment.
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There might be hidden fees. Costs for implementation, extra support, or going over your usage limits might not be clear from the start.
This lack of transparency is frustrating. It’s hard to build a business case for a new tool when you can’t even find out what it costs without getting on a sales call.
By contrast, eesel AI has transparent and predictable pricing. All the plans are laid out right there on the website, so you know exactly what you’re paying. There are no sneaky per-resolution fees, so a busy month won’t lead to a surprise bill. Plus, you can choose a month-to-month plan and cancel anytime. It’s just a more straightforward, customer-friendly way of doing things.
A visual of the eesel AI pricing page, which contrasts with the opaque pricing models of Decagon vs Forethought.When Decagon vs Forethought aren't the right fit
So, what's the bottom line? Decagon and Forethought are powerful, no doubt. But they’re built for a certain kind of customer: a large company with the budget, time, and developer resources to take on a big implementation project.
But what if you need that same level of power without all the enterprise baggage? What if you want to move fast, stay in control, and know what you're paying for?
That’s where eesel AI comes in. It’s built to solve the same core problems, just with a totally different philosophy.
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Go live in minutes, not months. Instead of a long, drawn-out deployment, you can set up eesel AI yourself and start seeing results on the first day.
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You're in the driver's seat. You get fine-grained control over what your AI does. Use a simple prompt editor and automation rules to define your AI's behavior, and test it safely in simulation mode.
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All your knowledge in one place. Connect to everything instantly. eesel AI works with your helpdesk, whether it's Zendesk or Intercom, but it also pulls knowledge from wikis like Confluence, documents in Google Docs, and even public Slack conversations.
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No more pricing mysteries. You know exactly what you're paying with clear, flexible plans that grow with you.
An infographic illustrating how eesel AI centralizes knowledge from different sources, a key differentiator in the Decagon vs Forethought comparison.Decagon vs Forethought: Choosing an AI partner, not just a platform
The choice between Decagon vs Forethought really comes down to a choice between two very capable, but also very complex and expensive, enterprise AI platforms. For a lot of modern support teams, the best tool isn't the heaviest one, it's the smartest and most agile one.
Your AI tool should feel like a part of your team, not another massive project on your plate. It should give you powerful automation without making you overhaul your workflows or wait months to see it in action. Ultimately, it should give you the confidence to automate safely and the transparency to know you’ve made a good investment.
Ready to see how fast and simple AI support can be? Get started with eesel AI today.
Frequently asked questions
Decagon focuses on building highly sophisticated, generative AI agents for complex, multi-step issues, often requiring engineering involvement. Forethought offers a broader suite of tools including full automation, ticket triage, and human agent assist, often with a no-code builder for workflows.
Both Decagon vs Forethought are enterprise platforms, meaning their implementation typically involves a guided setup process that can take weeks or even months to fully get up and running. This "heavy lift" is common for high-touch enterprise software.
When looking at Decagon vs Forethought, expect high, custom pricing that is not publicly disclosed, often starting in the tens of thousands annually. They typically involve long-term contracts and may include additional costs for implementation or exceeding usage limits.
Generally, Decagon vs Forethought are not ideal for teams needing rapid deployment. Their enterprise nature involves extensive setup and implementation times, which means showing quick results can be challenging.
Decagon often requires significant engineering support to integrate with internal tools and APIs for its generative AI agents. While Forethought offers no-code tools like Autoflows, both are enterprise platforms and may still benefit from technical expertise for optimal setup and integration.
Both Decagon vs Forethought include built-in safety measures, but configuring these can be complex. There can be uncertainty about how the AI will behave in live customer interactions until it's fully deployed and actively used.
