Build an AI delivery workflow with Make
A small goal: turn one manual delivery into four nodes before deciding whether to productize it.
Best use case
Use this when you know the deliverable but still collect material, process output, email results, and log feedback by hand.
Workflow nodes
4
Form, AI, email, log
Manual work saved
30%+
Less copying and sorting
Sales sample
1
Show clients a full delivery chain
Public case breakdown
How Stellantis &You UK used Make for aftersales messaging
The aftersales team was overloaded by phone and in-person communication. In Make's case, intent and sentiment classification routed ordinary messages to automation and subtle dissatisfaction signals to human follow-up.
Source
Make customer care success story47,000+ messages analyzed and 18,000+ handled automatically over 12 months
It did not start as a huge system
Classify first
The workflow judges intent and sentiment before attempting any response.
Keep human boundaries
Negative, ambiguous, and risky messages are escalated to people.
Track outcomes
The team measures handled volume, escalation, and customer feedback instead of showing only a workflow diagram.
What to copy
Sell saved time, not the diagram
Clients buy less repeated work and fewer missed issues, not the automation canvas.
Automate low-risk work first
Classification, sorting, notification, and logging are safer first steps than full auto-replies.
Price from before-after evidence
Record manual time and post-automation time before quoting a pilot.
Build a small version
Collect 20 historical messages
Pick one niche such as clinics, training firms, or local services.
Create 3 labels
Use only no reply needed, needs human, possible churn.
Run 5 reviewed tests
Let AI classify, review manually, then calculate accuracy and time saved.
Do not promise fully automated support first. Message triage and human alerts are easier pilots to sell.
Workflow blueprint
Build the shortest workflow first. Each node should solve one action.
Form trigger
Receive material from Tally, Typeform, or your site.
AI processing
Turn material into summaries, categories, scores, or drafts.
Result delivery
Send the result to the user, team, or your inbox.
Feedback log
Save output, timing, and feedback to a table or work tool.
Build it in 60 minutes
Map the manual process
Write the 5 actions needed to deliver the result once.
Automate 2 repeated actions
Start with copying, sorting, notification, and logging.
Add human review
Send AI output to yourself before sending it to a client.
Record time saved
Compare the old delivery time with the automated flow.
Copy-ready delivery note
Intro
After you submit the material, I will use an automation workflow to organize it and then manually review the result.
Final screen
If the sample helps, I can turn this into a monthly workflow maintenance service.
How to read the result
Continue
The flow runs 5 times, manual correction is under 30%, and users keep submitting material.
Narrow scope
The flow works but client material varies too much. Narrow by industry or file type.
Pause
Every run requires heavy judgment and cannot be reused.
Connect it to the action plan
Step 1
Collect material with a form.
Step 2
Use Make for processing and delivery.
Step 3
Review output manually.
Step 4
Use time saved in your pricing.
Build an AI delivery workflow with Make
This tutorial helps with the current action and does not promise income.