Building a custom AI chat experience sounds great in theory, doesn’t it? You picture this smart, slick bot that wows your customers, solves their problems instantly, and generally makes life easier for everyone. But then reality hits, and you run smack into the first big hurdle: authentication and security.
Suddenly, that fun chatbot project turns into a headache of managing tokens, securing endpoints, and writing a ton of server-side code you didn’t plan for.
Frameworks like ChatKit were a common starting point for this kind of project back in the day. Its approach, especially ChatKit JS Authentication, was a very developer-heavy way of building chat. It gave you control, sure, but it also dumped a whole lot of complexity on your plate.
This guide will walk you through how ChatKit JS Authentication actually worked, dig into the hidden frustrations of that approach, and show you a much simpler, more powerful way forward with modern AI platforms that can get you up and running in minutes, not months.
What is ChatKit JS Authentication?
Let’s take a quick trip back in time. Before it was retired and its ideas were folded into newer tools, ChatKit was a framework from Pusher that let developers bolt chat features onto their apps. At its heart, ChatKit JS Authentication was a security model built to do one thing: keep your secret API keys from ever being exposed in a user’s browser. Instead of pasting a secret key into your frontend code (which is a huge security risk), it used a system of temporary tokens.
Here’s a simple breakdown of how it all went down:
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Asking for permission: A user shows up on your site, and the chat widget needs to connect. First, it sends a request to your company’s backend server, essentially asking for permission to join the chat.
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Validating the user: Your server gets the request. Now it’s on your server to figure out if this user is legit. This could mean checking if they’re logged in, looking for a cookie, or some other kind of verification.
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Generating a token: Once your server confirms the user is who they say they are, it uses its secret API key to chat with the ChatKit service. It asks for a temporary, secure session token just for that specific user.
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Passing the token along: The ChatKit service creates this short-lived token and sends it back to your server. Your server then passes it down to the user’s browser.
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Making the connection: The ChatKit component in the browser now has a temporary key. It uses this token to open a secure connection directly with the ChatKit service.
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Rinse and repeat: Because the token expires quickly (for security reasons), this whole dance has to happen again right before it expires to keep the chat session going.
This flow keeps your main API key safe and sound on your server. But as you can probably tell, it also puts a lot of the work squarely on your shoulders.
The challenges of custom-building with ChatKit JS Authentication
While using tokens is a standard security practice, frameworks like ChatKit pretty much left the entire implementation up to you. This DIY approach might sound like it offers complete freedom, but it comes with some serious downsides that teams often don’t discover until they’re already deep in the project.
The heavy load on developers
Right out of the gate, that whole authentication flow requires a dedicated backend developer. It isn’t an out-of-the-box feature. You need an engineer to build, deploy, and maintain a server endpoint just to hand out and refresh tokens. That’s time and talent being pulled away from your actual product and poured into building chat plumbing.
This is a huge time sink, especially when you compare it to how modern tools work. An integrated platform like eesel AI, for example, skips all that backend work by plugging directly into your existing help desk with one click. It securely manages user authentication and integration without your team having to write a single line of server code, so you can focus on fine-tuning the AI, not building the pipes.
Ongoing security and maintenance work
When you build the authentication logic yourself, you also own all the security risks that come with it. You have to protect your secret key, make sure tokens are set to expire properly, handle the refresh logic without any hiccups, and protect the endpoint from attacks. One tiny mistake in your code could expose user conversations or create a major vulnerability.
And on top of all that, you’re responsible for maintenance. As the underlying chat SDK or its APIs changed (which they did), it was up to developers to update their code to keep things from breaking. This locks you into a never-ending cycle of updates and bug fixes, which only adds to the real cost of the tool.
Just the tip of the iceberg
Let’s say you successfully build a secure chat widget. Great! But that’s all you have: a chat window. The actual value comes from the intelligence powering it, and that’s something frameworks like ChatKit never provided.
You were still left to figure out:
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How to hook it up to your knowledge sources so it could actually give helpful answers.
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How to set up rules for when the bot should handle a question versus when it needs to pass it to a human.
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How to build any kind of analytics to see how it’s doing and where your knowledge gaps are.
This is where older frameworks really fell short. They gave you the parts to build a chat interface, but not the complete AI support engine that a business actually needs.
A better way: Integrated AI platforms
Thankfully, the world has mostly moved on from these developer-heavy frameworks. The focus now is on fully-managed, self-serve AI platforms. These tools are built for support, sales, and IT teams, not just engineers. They offer a much faster, more secure, and way more powerful method for getting AI chat live.
eesel AI is a perfect example of this modern approach, and it was specifically designed to solve the headaches of the old way.
Go live in minutes with one-click integrations
Instead of your team spending weeks on backend development, eesel AI is completely self-serve. You can sign up, connect your tools, and have a working AI agent running in just a few minutes, without ever having to talk to a salesperson.
You can forget about building a token server. With eesel AI, you just connect your help desk, whether it’s Zendesk, Freshdesk, or Intercom, with a single, secure click. All the tricky authentication and integration work is done for you, so you can jump right into creating a great customer experience.
Unify your knowledge beyond the help center
A chat framework is just an empty box. An integrated platform like eesel AI comes with intelligence ready to go. It doesn’t just read from a static help center; it connects all of your scattered knowledge sources almost instantly.
eesel AI learns from your team’s past tickets and macros, so it can adopt your brand voice and understand common resolutions right from the start. It also integrates with the tools your team already relies on, like internal docs in Confluence and Google Docs or product info in Shopify. This allows it to be deeply context-aware without anyone having to manually copy-paste data.
eesel AI connects to all your knowledge sources, from help desks to internal docs, eliminating the manual integration work required by older frameworks that relied on methods like ChatKit JS Authentication.Get full control with a customizable workflow engine
One of the biggest worries with AI is losing control. But modern platforms are designed to put you in charge. With eesel AI’s powerful workflow engine, you get fine-grained control over exactly how your bot behaves.
Modern platforms like eesel AI provide a customizable workflow engine, a significant improvement over the basic ChatKit JS Authentication which required manual coding for any custom behavior.You can use a simple prompt editor to shape the AI’s persona, its tone of voice, and the specific actions it’s allowed to take, from tagging a ticket to looking up live order information with a custom API call. More importantly, you can roll it out confidently. You could start by having the AI automate just one or two simple kinds of tickets and have it safely escalate everything else to your human agents. As you get more comfortable, you can slowly expand what it handles, all while keeping an eye on its performance in a clear, straightforward dashboard.
Build vs. buy: ChatKit JS Authentication vs. eesel AI
For any team trying to decide what to do, it really comes down to building a solution from scratch versus buying an integrated platform. Here’s a look at how the two paths compare.
Comparing key features and capabilities
Putting them side-by-side makes the difference pretty obvious. The framework approach requires a big technical investment for every single feature, while an integrated platform gives you those features right away.
| Feature | Building with a Framework (like ChatKit) | eesel AI Integrated Platform |
|---|---|---|
| Setup Time | Weeks to months (requires backend & frontend coding) | Minutes (self-serve, one-click integrations) |
| Authentication | You have to manually build and secure a token server | Handled automatically and securely through the help desk integration |
| Knowledge Sources | You need to build custom integrations for every source | One-click connections to help desks, wikis, docs, and more |
| Automation Workflows | Must be coded from scratch (tagging, triage, escalation) | Built-in, customizable workflow engine for actions and routing |
| Testing & Simulation | Manual testing, no built-in way to simulate | Powerful simulation mode over historical tickets to forecast performance before you go live |
| Maintenance | Constant developer work to manage servers, security, and updates | Fully managed by eesel AI, with constant improvements |
The real cost of building it yourself
A library like ChatKit might have been technically "free," but the final bill tells a very different story. The hidden costs start to pile up fast:
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Developer Salaries: The cost of engineers spending weeks or months on the initial build, plus all the ongoing maintenance.
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Server & Infrastructure Costs: The price of hosting the authentication server and any other backend services needed to power the bot.
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Opportunity Cost: Every hour your developers spend on chat infrastructure is an hour they aren’t spending on your main product.
This is completely different from eesel AI’s transparent pricing. For a predictable monthly fee, you get the whole platform, the infrastructure, the security, and all future updates included. There are no surprise per-resolution fees that punish you for doing well. It frees up your tech team to focus on what they do best, while giving your support team the tools they need to shine.
Move beyond ChatKit JS Authentication to intelligent platforms
So, where does that leave us? Building support AI from the ground up with tools like ChatKit had its time and place, but it’s just not the smartest way to do things anymore.
Today’s businesses need more than a chat window; they need an intelligent, integrated platform that can automate workflows, bring all their knowledge together, and start delivering value in minutes. This new generation of tools lets support teams build, manage, and grow their own AI agents without having to get in a long line for engineering resources.
eesel AI is the perfect example of this modern approach. It’s powerful enough for complex business needs but simple enough for anyone to get running in an afternoon. Instead of wrestling with authentication tokens and server code, you can focus on what really matters: giving your customers faster, smarter, and more personal support.
Ready to launch your AI agent in minutes, not months? Try eesel AI for free.
Frequently asked questions
It required developers to build and maintain a custom backend server endpoint to generate and refresh temporary session tokens. This added significant engineering overhead compared to integrated solutions.
The main risks included potential exposure of secret API keys if not handled correctly, ensuring tokens expired properly, and protecting the token-issuing endpoint from attacks. Developers were solely responsible for maintaining the security of this custom code.
It managed permissions by having your backend server validate users and then request a temporary, secure session token from the ChatKit service. This token was then passed to the user’s browser to establish a secure connection, keeping your main API key safe on the server.
ChatKit JS Authentication is no longer recommended because it was a developer-heavy approach that offloaded significant backend, security, and maintenance work to your team. Modern integrated AI platforms offer a much faster, more secure, and comprehensive solution without custom coding.
Beyond authentication, you still needed to integrate knowledge sources, define bot-to-human escalation rules, and build analytics from scratch. ChatKit JS Authentication only provided the chat interface framework, not the AI intelligence or operational workflows.
Systems built with ChatKit JS Authentication demanded constant developer work for server management, security updates, and adapting to SDK changes. In contrast, modern platforms like eesel AI are fully managed, handling all maintenance and updates automatically for a predictable cost.
