Messy inputs to AI schema
Synthetic emails, forms, notes, and spreadsheet rows become a structured schema with uncertainty kept visible.
Synthetic examples
Example AI-enabled workflow improvements without client data.
These examples show the type of practical improvement DG Workflow is being built around. They use fake private-sector data, not real client records, testimonials, or confidential business information.
Spreadsheet to reporting view
Messy spreadsheet inputs can be cleaned into a repeatable reporting flow before any dashboard or automation is added.
Document or email to action list
Repeated messages, notes, or documents can become draft actions for review instead of being copied manually between tools.
See it in action
Messy input to reviewable action.
One synthetic private-sector engineering example showing the breadth of the work: AI extraction, structured data, human review, automation, website updates, and reporting.
Step 1 of 5
Start with the real mess.
The synthetic workshop receives job details across a website form, an email reply, a phone note, and a spreadsheet row.
01
Messy input
02
AI schema
03
Review
04
Automations
05
Outputs
Mixed inbound request
Synthetic dataWebsite form
Need repeat batch of aluminium pump brackets, around 40 units. We used you last year. Can someone confirm lead time?
Email reply
Drawing attached says rev B but PO draft says rev A. Material should be 6082-T6. Delivery wanted by next Thursday if possible.
Phone note
Caller asked whether the website lead-time page is still accurate. Mentioned tolerance on the slot is tighter than the old job.
Spreadsheet row
Northline Precision | repeat? yes | qty 40 | owner Sam | source web | value unknown | status waiting
AI extraction schema
WaitingRun extraction to create the schema.
The source messages stay visible. The AI step is only useful once it creates a repeatable structure.
Review and outputs
Human reviewReview flags appear after extraction.
The workflow should make uncertainty harder to miss, not hide it behind confident-looking output.
Sources parsed
0
website, email, phone, sheet
Schema fields
0
repeatable job-intake shape
Review flags
0
kept out of automation until checked
Outputs ready
0
after human review gates
CRM-style record
Pending
Internal tasks
Pending
Customer reply
Pending
Website note
Pending
Report row
Pending
Proof posture
Credible before case studies.
Until real client work is approved, delivered, and permissioned, the site will use labelled synthetic demos. That keeps the public proof useful without inventing results or exposing private data.