CoSupport AI 2.0: Agentic AI in Customer Service

CoSupport AI 2.0, released in June 2026, lets the AI agent act as well as answer. It reasons in several steps before replying, logs every decision, and through the new Agentic API can cancel a subscription, process a refund, or update an order inside your systems. On 1.x, the average AI resolution rate was 74%. On 2.0 it reaches up to 85%.

What's new in CoSupport AI 2.0

• Multi-step reasoning. The AI searches, analyzes, searches again, and validates before it answers. Beta users report a 15–20% gain in response accuracy on complex tickets.
• Decision logs. Every AI reply comes with a log of the reasoning, the actions taken, and the sources used.
• Agentic API. The AI can act in external systems in real time: update orders, cancel subscriptions, process refunds, and pull account-specific information.
• 12 new integrations, including Shopify, Stripe, Notion, and Confluence. Knowledge source connectors grew from 7 to 15.

What makes AI "agentic"

There's a difference between an AI that tells a customer how to cancel a subscription and an AI that cancels it. Both give an answer. With the first, the customer still has to do something. With the second, the issue is resolved: no follow-up, no click path, no chance of getting stuck halfway.

Conversational AI generates text. It reads a question and writes an answer, and acting on that answer is up to the customer or an agent. Agentic AI reads the question, works out what needs to happen, calls the right system (your helpdesk, CRM, or payment processor), performs the action, and confirms it, all in the same conversation.

The technical piece that makes this possible is an action layer: an API that connects the AI's reasoning to the systems your business runs on. CoSupport AI 2.0 added this as the Agentic API. It's part of customer service automation that closes tickets end to end.

How multi-step reasoning changes accuracy

The single-search problem

First-generation AI support works like this:

1. The customer sends a message.
2. The AI searches the knowledge base for the most similar content.
3. The AI writes a reply based on that content.

Step 2 is where it breaks. Take "Why was I charged twice this month?" The AI has to understand the question, find the billing policy, check the account, and validate the answer. One search either finds the right content or it doesn't. If the question maps cleanly to one document, like a return policy FAQ, that works. Real tickets are rarely that clean.

"I need to cancel my subscription, but I was already charged for next month" touches billing, cancellation policy, and refund eligibility, possibly three separate knowledge base sections. A single search usually finds one of them, and the reply comes out partly right. The AI had incomplete information because it never looked past its first search.

What the AI does now

In 2.0, CoSupport AI Agent loops between searching and checking:

1. Reads the message and plans what it needs to find.
2. Searches for the first piece of information.
3. Checks whether that's enough or something is missing.
4. Searches again with a refined query if there are gaps.
5. Validates the combined information against the original question.
6. Writes the reply once the reasoning is complete.

Think of two support agents. One opens the first FAQ and starts typing. The other reads the question, checks three sources, and makes sure the answer holds up before sending it.

The extra steps take time. In internal benchmarks, average response time went from 2.1 to 3.3 seconds. Early customers chose the accuracy gain over the extra 1.2 seconds: beta users report a 15–20% boost in response accuracy on complex tickets.

Where the improvement shows up

The gain is uneven across ticket types. It's clearest on:

• Multi-part questions, such as billing plus cancellation or account plus subscription.
• Questions where the customer didn't give all the context up front.
• Cases where the right answer combines two pieces of information from different documents.

For simple, single-topic tickets like "What are your business hours?" or "Where is my order?", the difference is small. One search handles those well, and the extra steps don't slow them down in any way customers notice.

Here's what that range means for a team with 500 tickets a month. At the 1.x average of 74%, about 130 tickets reach an agent. If 2.0 reaches the top of its range at 85%, about 75 do. Your own rate depends on your knowledge base and connected systems, and a pilot measures it on your tickets.

Decision logs: seeing why the AI answered

Every AI reply in 2.0 comes with a decision log: the reasoning steps, the actions taken, and the data sources used. Support leads and QA teams can check AI behavior ticket by ticket, see exactly where an answer came from, and find areas to improve faster.

What agentic AI can do in support

Agentic AI handles tickets where the resolution is an action:

• Subscription management. A customer wants to cancel, downgrade, or pause. CoSupport AI Agent processes the request through your billing integration, confirms the change, and closes the ticket.
• Order management. A customer wants to change or cancel an order, or asks for a refund. With the Shopify integration, the AI checks eligibility and makes the change without an agent touching the ticket.
• Account-specific answers. Some questions need live data, such as "Did my payment go through?" Agentic AI queries the relevant system and builds the answer from real account data.
• Escalation with context. When a ticket needs a person, the AI collects the order number, account details, and issue history first, so the agent doesn't have to ask the customer to repeat anything. From there, CoSupport AI Assistant drafts replies and surfaces relevant documentation for the agent.

What agentic AI can't replace

Some tickets still belong with people. Billing disputes with conflicting claims, questions that need legal or compliance judgment, and customers in real distress still need a person.

In practice, agentic AI takes the L1 tickets that require an action, and agents handle L2 and L3, where the right action isn't clear from the data. What changes is the scope of L1. It used to mean simple information requests. With an action layer, it also covers many transactional requests that reached agents only because no tool could finish them end to end.

The integration requirement

Agentic AI is only as capable as the integrations behind it. An AI agent connected only to your knowledge base can write good answers. Connected to your helpdesk, your Shopify store, and your billing system, it can close tickets on its own.

That's why integration depth matters more for agentic AI. The ceiling for conversational AI is the quality of your documentation. The ceiling for agentic AI is the quality of your connected systems.

These work alongside existing helpdesk integrations such as Zendesk and Freshdesk. The Zendesk integration carries over unchanged, and the Shopify integration works on standard Shopify, Shopify Advanced, and Shopify Plus.

How to get CoSupport AI 2.0

All new accounts created after June 10, 2026, run on 2.0 by default. Existing clients move to 2.0 through a free migration, and their training data and tuning carry over. You can test 2.0 on your own tickets in a free pilot and read the full 2.0 release notes.

What changes for support teams

When a team moves from conversational to agentic AI, the type of ticket the AI resolves changes. Conversational AI resolves information requests. Agentic AI also resolves action requests.

Agents spend less time on subscription cancellations, order updates, and refund requests, because the AI completes many of them. What's left is the work that needs human judgment: edge cases, account investigations, and conversations where empathy matters more than speed.