← Back to blog

Build a triage workflow with AI in minutes

Describe what you need in plain language and let AI draft the workflow graph — then edit any step. Triggers, KB-grounded steps, branches, tools, code, and clean handoffs.

Written by

WisebotAI

Published

June 9, 2026

Workflows are where repeatable work stops living in someone's head. On WisebotAI a workflow is a drag-and-drop canvas — but you don't have to start from a blank one. Describe what you need and AI drafts the graph, then you edit any step in plain language.

Start by describing it

When a new conversation comes in, search our knowledge, classify it as billing / technical / sales, answer the easy ones, and route the rest to the right team with the transcript.

AI turns that into a connected graph of nodes. You review it, tweak wording, and publish. Editing later is the same: "add a step that posts escalations to the #support Slack channel" and the graph updates.

The node types you'll actually use

  • Trigger — webhook, scheduled/timer, manual run, a public form link (/f/{workflow}), or an agent.
  • KB search — pull grounded, cited context from your knowledge base.
  • LLM / agent step — reason over the input with the model you choose (GPT or Claude), with tools attached.
  • Manager / condition branch — classification-based or if/else routing.
  • HTTP — call any REST API (GET/POST/… with auth).
  • MCP tool — call a connected system (Slack, Notion, your CRM).
  • Code step (E2B) — run Python, Node, or Bash in a sandbox when logic outgrows no-code.
  • Output / hand off — return text, JSON, or a generated PDF/PPTX, or hand to a person.

A triage flow, end to end

  1. Trigger: new conversation.
  2. KB search → LLM: draft a grounded answer and a category.
  3. Manager branch: billing | technical | sales.
  4. Billing: call the CRM connector to pull the account; if balance is sensitive, approval gate before any change.
  5. Technical: if confidence is low, hand off to the engineering queue with context.
  6. Sales: post to #sales via the Slack connector and create a lead.
  7. Every branch leaves a run record you can open and review.

Why "visible" matters

Automations that hide in a black box are impossible to trust or debug. Here every published run leaves a trail — inputs, the path taken, each step's output — so ops and leadership get the audit story, not just developers.

Tips

  • Keep branches shallow. Two or three clear paths beat a sprawling tree.
  • Ground before you act. Put a KB step before any tool call so actions are based on real context.
  • Gate the irreversible. Refunds, deletions, external messages — approval-gate them.

Next: tool calling with MCP for the connectors above, and writing agent system prompts for the LLM steps.