How we build AI workflows

Step 1 — Identify the repeated inquiry

We look for questions that appear often and follow a predictable pattern, such as:

• "What service is right for me?"
• "How much does this cost?"
• "Can you send the intake form?"
• "What happens after I book?"
• "Do you support my industry?"
• "Can I reschedule?"

The best first AI workflow is usually not the most complex one. It is the one that happens often enough to create measurable time savings.

Step 2 — Build the approved knowledge base

We collect and organize approved source material, such as:

• Service descriptions
• Pricing rules or ranges
• FAQs
• Policies
• Intake instructions
• Email templates
• CRM notes
• Internal process documents

The AI is instructed to answer only from approved knowledge. If it cannot answer confidently, it escalates to a person.

Step 3 — Add human review

For low-risk questions, the AI may draft a response for staff to review. For sensitive questions, it may summarize the inquiry and recommend next steps without sending anything automatically.

This keeps your team in control while still reducing repetitive work.

Step 4 — Connect the workflow

Depending on the business, the workflow can connect to:

• Website forms
• Shared inboxes
• CRM systems
• Calendars
• Support tools
• Internal documents
• Spreadsheets
• Task management systems

The system should fit the way your team already works.

Step 5 — Measure the result

We define success before launch. Typical metrics include:

• Time saved per inquiry
• Response time
• Number of inquiries resolved
• Number of escalations
• Staff edits required
• Customer satisfaction
• Error rate

If the workflow saves time and maintains quality, we expand. If not, we improve the knowledge base, rules, or review process before scaling.