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Traditional automation tools like Zapier, n8n, and Power Automate wire specific fields between APIs. When an API changes, a field gets renamed, or a response structure shifts, the workflow breaks. Someone has to find the broken mapping and fix it manually. Agentic Automation takes a different approach. Instead of wiring fields, you describe what each step should do in natural language. AI resolves the data mapping at runtime, so workflows adapt to changes instead of breaking.
Workflows vs. agents: Agents handle conversations (Slack, Teams, chat). Workflows handle backend automation triggered by events (webhooks, schedules, emails). Both are built in xpander, but they solve different problems.

How it’s different

Traditional automation maps specific fields: response.data.contact.emailinput.recipient. If the API restructures, the mapping breaks. Agentic automation describes intent: “Send the enrichment results to the assigned sales rep.” This works regardless of response structure.
Workflow canvas

A workflow with triggers, classifier routing, branching actions, and output nodes.

Build with canvas or SDK

The visual canvas is built for ops teams, business analysts, and IT admins who want to build workflows without writing code. Drag nodes, connect them, and deploy. Developers can use the Python/JS SDK instead. Same runtime, same workflows, but with version control, testing, and programmatic composition. Workflows built on the canvas can also be invoked via the SDK, so both audiences work on the same system.

What you can build

Workflows mix AI reasoning with deterministic logic in the same flow. Some steps use an LLM to classify intent, summarize data, or make decisions. Others run without one to call an API, send an email, extract text via OCR, or run custom code. You combine both depending on what the step needs. Workflows are triggered by webhooks, schedules, API calls, inbound emails, or chat messages. Here are the kinds of multi-system processes they handle well:

Agentic context

Workflows maintain state across runs. If you run a lead enrichment workflow daily, it doesn’t reprocess every lead from scratch. It stores previous results, processes only new records, flags changed data, and adapts if the API schema changes between runs. This is what makes agentic automation “self-adapting.” The workflow understands what it did last time and adjusts accordingly.

Security and versioning

Every deployment is an immutable snapshot. If something goes wrong, you roll back with one click. Secrets are injected at infrastructure level (never exposed to the model), access is controlled via RBAC, and every action is audit-logged. Run entirely in your VPC or air-gapped if needed.

What’s next

Building Workflows

Step-by-step guide to the visual canvas.

Triggers

Configure webhooks, schedules, and other trigger types.