Six workflows that Maestro Automate is built for, from order intake to screening checks, with the nodes each one uses.

Maestro Automate is built for workflows where something comes in, an AI agent decides what to do, and APIs carry out the decision, all within minutes or hours. Each use case below follows that pattern. The first one is the example that What is Maestro Automate? walks through and Your first workflow builds.

What happens: an order or a sales lead arrives. An agent validates it, checks stock and the customer's credit over API, and creates the order in the ERP or customer relationship management (CRM) app.

You'll use: a connector trigger, HTTP Request, an Autonomous Agent, a Decision, and connectors.

What happens: a first notice of loss arrives, which is the first report of an insurance claim. An agent classifies its severity, checks the coverage against the policy system's API, and routes the claim to the right adjuster's queue.

You'll use: a connector trigger, an Autonomous Agent, HTTP Request, a Switch to route by severity, and queue nodes.

What happens: an employee asks for help, for example a password reset or access to an app. An agent reads the request, pulls the employee's context from the identity, IT service management, and human resources (HR) systems over API, decides what to do, and resets the password, grants the access, or opens a ticket the same day. The request can also come in through chat or a phone call (Preview).

You'll use: an Autonomous Agent or a Conversational agent (Preview), HTTP Request, and connectors. Build a chat agent workflow builds a version of this.

What happens: an invoice arrives as a document. A document extraction step reads its fields, an agent checks them against the purchase order over API, and the invoice is posted when it matches.

You'll use: Extract (Preview), an Autonomous Agent, HTTP Request, and a Decision.

What happens: APIs pull both sides of a transaction, for example the bank record and the ledger entry. When they don't match, an agent explains the difference and proposes a fix, and the workflow either applies the fix over API or opens a case for a human.

You'll use: HTTP Request, an Autonomous Agent, a Decision, and connectors.

What happens: a new customer signs up. An agent runs sanctions and adverse-media lookups over API, scores the result, and writes the score back to the customer record. Customers with a match are flagged for review.

You'll use: a connector trigger, HTTP Request, an Autonomous Agent, and a Decision.