An autonomous agent's intelligence is only half the story. A brilliant mind, capable of complex reasoning and planning, is of little use if it's trapped in a digital box, unable to interact with the real world. For a digital worker to create tangible value, it needs more than an objective—it needs tools. This is where integrations come in, transforming an agent from a theoretical thinker into a practical, high-impact member of your workforce.
At Agents.do, we understand that an agent's power is directly proportional to its ability to connect with and act upon the systems your business already uses. Let's explore how critical integrations, like those for Zendesk and Shopify, can supercharge your autonomous agents and turn complex business processes into seamless, automated services.
Imagine hiring a top-tier customer support specialist. They're smart, empathetic, and an expert problem-solver. Now, imagine putting them in a room with no phone, no computer, and no access to your company's software. They have the potential to be great, but they lack the means to apply their skills.
A standalone AI agent is in the same position. Without access to external systems, it can't check an order status, update a customer ticket, or process a refund. It's a brain without hands. The true potential of business automation is only unlocked when we bridge the gap between the agent's cognitive abilities and the business applications where work actually happens.
This is precisely where the integrations property in an agent's definition becomes its most powerful feature. Look at the simple, declarative code for creating a customer support agent on the Agents.do platform:
import { Agent } from 'agents.do'
// Create a customer support agent
const customerSupportAgent = Agent({
name: 'Amy',
role: 'Customer Support Agent',
objective: 'Handles customer inquiries and resolves common issues',
integrations: ['chat', 'slack', 'email', 'zendesk', 'shopify'],
triggers: ['onTicketCreated', 'onMessageReceived'],
searches: ['FAQs', 'Tickets', 'Orders', 'Products', 'Customers'],
actions: ['sendMessage', 'updateOrder', 'refundOrder', 'resolveTicket', 'escalateTicket'],
})
That one line—integrations: ['chat', 'slack', 'email', 'zendesk', 'shopify']—is the key. It equips "Amy" with the digital hands she needs to perform her job. She's no longer just thinking about customer support; she's actively participating in it.
Let's walk through a common e-commerce scenario to see how these integrations work in concert:
Trigger (Zendesk): A customer creates a new support ticket in Zendesk. The message reads, "I haven't received my order #ORD-5678, can you tell me where it is?" The onTicketCreated trigger on Amy's agent definition is activated.
Perception & Planning (Agents.do Core): Amy receives the ticket data. Its core objective is to "Handle customer inquiries." It parses the message, identifies the customer's intent ("order status inquiry"), and extracts the key entity ("order ID: #ORD-5678"). Amy knows it needs to look up this order.
Action (Shopify): Amy uses its shopify integration. It accesses the Orders data source specified in its searches and queries for order #ORD-5678. Shopify returns the order status: "Shipped," along with the tracking number "1Z987XYZ."
Execution (Zendesk): Armed with the correct information, Amy uses its zendesk integration. It executes the sendMessage action to post a reply directly to the customer's ticket: "Hi there! I've checked on your order #ORD-5678. It has been shipped and you can track its progress here: [link to carrier with tracking #1Z987XYZ]. Let me know if you need anything else!"
Resolution (Zendesk): Amy then executes the resolveTicket action, marking the ticket as solved in Zendesk.
In a matter of seconds, a complete, multi-step, cross-platform business process has been executed without any human intervention. This is the power of an integrated autonomous workforce.
But what if the problem is more complex? What if the customer's ticket was, "My order #ORD-5678 arrived damaged"?
This is where another core feature of the Agents.do platform shines: agent collaboration.
Amy's logic would determine this issue falls outside of a simple status check. Instead of resolving the ticket, it uses its escalateTicket action. But it doesn't escalate to a human—it escalates to another specialized agent.
Amy can delegate the task to "Fin," a finance and refunds agent. Fin's agent definition might look like this:
const financeAgent = Agent({
name: 'Fin',
role: 'Finance & Refund Specialist',
objective: 'Processes refunds, reconciles transactions, and handles billing inquiries',
integrations: ['shopify', 'stripe', 'quickbooks'],
actions: ['refundOrder', 'issueStoreCredit', 'generateInvoice'],
})
When Fin receives the escalated task from Amy, it uses its shopify integration to execute the refundOrder action for order #ORD-5678. It might then notify a logisticsAgent to document the damaged goods. Once the refund is processed, Fin informs Amy, who then updates the customer in Zendesk, confirming their refund and closing the loop.
The beauty of the Agents.do platform is that this incredible complexity is orchestrated through simple, declarative APIs. As a developer, you practice Business-as-Code. You don’t need to manage the intricacies of API authentication, state management, or the sequence of operations.
You simply declare:
The platform orchestrates the how, allowing you to build, deploy, and scale a powerful team of digital workers that are deeply embedded within your existing business workflows.
Zendesk and Shopify are just the beginning. Any business process, from sales outreach in Salesforce to data analysis in a Snowflake warehouse, can be automated by an integrated team of autonomous agents.
Ready to stop just managing business processes and start automating them? Deploy your first digital worker on Agents.do and discover what's possible when intelligence meets integration.