Zendesk advanced AI entity extraction: A practical overview

Let's be real, your support team is probably drowning in copy-paste work. Manually digging for order numbers, email addresses, and product codes in tickets isn't just boring, it’s slow, full of potential errors, and pulls your team away from actually helping people. It's the kind of repetitive task that wears people down and stops them from doing their best work.

This is exactly the problem entity extraction is supposed to solve. It’s an AI feature that automatically spots and organizes this key data, freeing up your agents to focus on more important things.

In this article, we’ll take a practical look at Zendesk's built-in entity extraction feature. We'll break down what it is, how it works, where it falls short, and what a more flexible and powerful alternative looks like.

What is Zendesk Advanced AI Entity Extraction?

Put simply, Zendesk Advanced AI Entity Extraction is a feature in Zendesk's Advanced AI add-on that automatically finds and labels specific bits of information (or "entities") inside of a customer message. Think of it as a smart highlighter for your support tickets and chats.

The whole point is to turn messy, free-form customer questions into structured, usable data. Once that information is organized, you can use it to automate workflows, get tickets to the right people, and give customers faster, more accurate answers.

Zendesk breaks entities down into two main types:

• Preset entities: These are ready to go right out of the box. They’re designed to identify common things like email addresses, credit card numbers, and social security numbers. No setup needed.

• Custom entities: These are the ones you have to build yourself for data specific to your business, like order numbers, tracking IDs, or unique product names. And yes, this is where the manual work comes in.

Key features and capabilities of Zendesk Advanced AI Entity Extraction

So, what can you actually do with this thing? Let’s get into its core functions and how they plug into the Zendesk system.

Preset vs. custom entities

Preset entities are handy for dealing with personally identifiable information (PII) without any fuss. If a customer accidentally pastes their credit card number into a message, Zendesk can spot and hide it automatically.

But for anything unique to your business, you'll need to create custom entities yourself. This is where things can get a bit technical. You'll need to set them up using methods like:

• Regular Expressions (RegEx): This is basically a sequence of characters that defines a search pattern. It's great for spotting predictable formats, like an order number that always starts with "ORD-" followed by five digits.

• Lists: You can also just feed it a list of words to look for, like all your product names or common problems such as "damaged" or "missing."

This setup can get complicated fast, especially if you're not comfortable with RegEx. It also means someone has to keep it updated. Every time a new product launches or an order number format changes, that person has to go back in and tweak the rules.

Sanitizing sensitive data

One of the most valuable uses for entity extraction is cleaning up sensitive data. You can set up Zendesk to automatically find an entity like a credit card number and replace it with a placeholder, like ``.

This is a huge win for compliance and security. It keeps sensitive customer info out of agent views and ticket histories, helping you meet privacy standards without anyone having to lift a finger.

Integration into conversation flows

The real magic happens when you use this extracted data to actually do something. Once an entity is identified, it becomes a piece of information your AI agents or automation rules can work with.

For example, if an AI agent spots an "order_number" in a customer's message, it can kick off an action to look up that order in your backend system. This lets the bot give a real-time status update without a human agent ever getting involved. The conversation shifts from a simple Q&A to an active, problem-solving one.

Practical use cases and benefits in customer support

It's one thing to talk about features, but what does this mean for your team's day-to-day? Here’s how entity extraction can make a real difference.

Automating ticket triage and routing

When set up correctly, entities can seriously clean up your ticket management. Imagine a ticket comes in that mentions a specific product name. You can create a rule that automatically sends it to the team that specializes in that product. No more manual assignments.

In the same way, if an entity related to "cancellation" or "refund" is found, the ticket can be automatically tagged as "Urgent" and bumped to the front of the line. This helps make sure high-priority issues get seen right away.

Powering more intelligent AI agents

With entities, your AI agent can become more than just a fancy FAQ page. It can understand not just what the customer wants (their intent), but also the specific details.

For example, a customer might write, "My new camera arrived broken." Instead of just passing the ticket to a human, a smarter AI agent can reply, "I'm sorry to hear that. Could you please provide the serial number from the bottom of the device?" It can then use entity extraction to check if the serial number format is valid before creating a return ticket.

Improving agent speed and accuracy

This isn't just for bots; it helps human agents too. Instead of an agent having to scan a long email thread for an order ID, that number can be pulled out automatically and placed in a custom field on the ticket.

It sounds like a small thing, but it has a big effect. It cuts down on average handle time by getting rid of the tedious search, and it prevents the copy-paste errors that lead to bigger problems down the line. This gives agents more time to focus on actually solving the customer's problem.

Limitations and challenges

While Zendesk's entity extraction is a move in the right direction, it has some friction points you should know about before diving in.

Setup is technical and time-consuming

Let's be direct: setting up and maintaining custom entities in Zendesk isn't for everyone. It often demands some technical know-how, especially with RegEx. This isn't something a non-technical support manager can usually set up on their own. The system is based on rules, which means it only knows what you tell it. It can't learn from past conversations or figure things out on its own.

Knowledge is siloed within Zendesk

This is probably the biggest drawback. Zendesk's AI works almost entirely on the information you've put into your Zendesk Help Center and the rules you’ve built.

The problem? Your company's most useful, up-to-date knowledge is likely scattered all over the place. What about the detailed troubleshooting guides in Confluence, the product updates in shared Google Docs, or the quick fixes your team shares in Slack? A customer's issue might have a solution sitting on an internal page that Zendesk's AI can't access, leading to a frustrating "I don't know" and an escalation that could have been avoided.

An infographic showing how eesel AI connects to multiple knowledge sources, unlike the siloed approach of Zendesk Advanced AI Entity Extraction.

The cost and commitment of an add-on

Advanced AI features aren't part of the standard Zendesk plans. You have to buy the "Advanced AI" add-on, which adds a noticeable cost per agent to your monthly bill. This can feel like you're being pushed deeper into one system instead of being free to pick the best tool for the job.

This is where a tool like eesel AI really changes things. Instead of a pricey, built-in feature that requires a platform upgrade, eesel is a flexible layer that connects directly to your existing Zendesk setup in just a few minutes. No big overhaul required.

Feature	Zendesk Advanced AI	eesel AI
Setup	Manual, rule-based (RegEx, lists)	Self-serve, learns from past tickets automatically
Knowledge Sources	Limited to Zendesk Help Center	100+ sources (Confluence, GDocs, Notion, etc.)
Integration	Built-in add-on requiring plan changes	One-click integration with your existing helpdesk
Testing	Limited, requires live deployment	Powerful simulation on historical tickets before go-live

Zendesk Advanced AI pricing

Zendesk sells its "Advanced AI" features as a paid add-on to their main Suite plans. According to their pricing page, you have to talk to their sales team or add it at checkout to find out the actual cost. This lack of clear pricing can make it tough to budget, since it's an extra fee on top of your base subscription.

This is a big difference from the straightforward and predictable pricing of eesel AI. Our plans aren't based on per-resolution fees, so you won't get a shocking bill after a busy month. You get all the key features included in your plan, and you can even start with a flexible monthly subscription that you can cancel anytime.

A screenshot of the eesel AI pricing page, highlighting its transparent and predictable costs.

Plan	Price (Billed Annually)	Key Features
Team	$239 / month	Up to 3 bots, 1,000 AI interactions/mo, Train on docs/websites
Business	$639 / month	Unlimited bots, 3,000 AI interactions/mo, Train on past tickets, AI Actions
Custom	Contact Sales	Unlimited interactions, Advanced actions, Custom integrations

A better approach: Unifying knowledge with eesel AI

eesel AI was built from the ground up to solve the exact challenges we've just talked about. It offers a smarter, more connected way to handle support automation.

Go live in minutes, not months

The biggest difference is our self-serve approach. You can connect your helpdesk, train your AI, and go live without ever talking to a salesperson or needing a developer to write complex RegEx rules. eesel AI's real advantage is its ability to train on your past tickets automatically. From the very first day, it starts learning your specific business context, your brand's tone of voice, and what information is important, all from your team's historical conversations.

A screenshot of the eesel AI platform showing how easy it is to train the AI on past tickets and various knowledge sources.

Unify all your knowledge, not just your help center

This is where eesel truly stands out. You can connect your AI to information from over 100 different sources, breaking down the knowledge barriers that hold most support bots back.

Here’s a simple example: A customer asks about a bug in a new "beta feature." Zendesk's native AI would search the public help center, find nothing, and be forced to escalate. An eesel AI agent, connected to your internal Confluence space, could find the relevant notes from engineering and provide a precise, helpful answer right away.

Test with confidence using risk-free simulation

Launching a new AI tool can feel like a bit of a gamble. With eesel AI's powerful simulation mode, you can take the guesswork out of it. Before you turn the AI on for live customers, you can run it on thousands of your past tickets in a safe environment. The dashboard will show you exactly how the AI would have responded, what data it would have pulled, and give you a solid forecast of your automation rate and cost savings.

The eesel AI simulation dashboard, which shows how the AI would have resolved past tickets, helping to forecast automation rates and savings.

Moving beyond basic Zendesk Advanced AI Entity Extraction

Zendesk Advanced AI Entity Extraction is a decent starting point for automation, but it’s hampered by a technical setup, siloed knowledge, and bundled costs that lock you into their ecosystem.

Today's support automation needs to be more powerful and flexible. The best tools are easy to set up, bring together knowledge from every part of your company, and work smoothly with the helpdesk you already use. eesel AI is the tool that delivers on that idea, turning your company's collective knowledge into your best support asset.

Ready to unlock automation that learns from all your company's knowledge? Try eesel AI for free or book a demo to see it in action.