Use case: unused fields
Field sprawl slows every change. Find the fields nothing uses, check whether records still hold data in them, and remove them through a governed change.
In one paragraph
Finding unused fields with SyncOnAI 360 means reading the dependency graph for references from code, automation, validation and layouts, checking live how many records hold a value, and calling a field unused only when the evidence is complete. Removal then ships as a proposal with checks, validation and approval.
01The problem
Every org has hundreds of fields that look unused. Nobody deletes them, because a field that looks unused might feed an integration, a report or a Flow nobody remembers.
No reference in Setup is not proof of no use.
A field nobody references may still hold years of data.
Objects approach their field limits while dead fields stay.
Every new change has to work around clutter.
02evidence
SyncOnAI 360 calls a field unused only when the source needed to prove it was read. If some code or automation could not be read, such as hidden managed package source, the result is unknown, with the reason.
That means the list of unused fields is one you can act on, and the unknowns tell you exactly what to check by hand.
03data
Ask how many records have the field populated, and the query runs live against the org. A field with no references but thousands of populated records needs a decision about the data before it goes.
Records are never stored by SyncOnAI 360.
04sprawl
The audit flags field sprawl on objects and custom fields without descriptions, and technical debt detection finds similar fields that may duplicate each other, explaining what looks alike.
Each finding carries an effort band and cost, so cleanup can be planned and priced.
05remove
Removal is a proposal with named checks, its blast radius and a validation against the org, approved by a second admin for production. Deploy to a sandbox first.
Rollback restores recorded metadata but cannot bring back deleted data, so the data decision comes first.
06audit
The audit's fields and data quality section flags fields nobody writes and fields with no references, alongside field sprawl on objects and custom fields without descriptions. Each finding carries its evidence, a severity and an estimated cost to clean up.
A check only runs when the data it needs was collected; a skipped check says so, and missing data is never reported as a pass.
07tools
Yes. Claude, Cursor and other MCP clients can look up a field and everything that depends on it through the read-only connection, with the same coverage statement on every answer.
That lets a developer check a field from the editor, while the removal itself still goes through a proposal in SyncOnAI 360.
08How it works
Evidence, data, decision, removal.
Find fields with no references and the unknowns.
Count populated records live.
Archive or accept the data loss.
Ship the removal as a checked proposal.
09Checklist
10Before and after
Without
With SyncOnAI 360
No reference in Setup, probably unused
Unused only with complete evidence
Data forgotten
Populated records counted live
Nobody dares delete
A list you can act on
Deletion straight in production
Checked, approved proposals
12Questions
Only when the source needed to prove it was read and nothing references the field.
Some source could not be read, so the tool cannot prove the field is unused. The reason is given.
Reports are synced metadata. The answer for each field states what was examined.
Yes, live against the org. Records are not stored.
No. Removal is a proposal you review and approve.
No. Rollback restores metadata, not data.
Technical debt detection finds similar fields and explains what looks alike.
Yes. Every plan includes every feature.
Yes. The audit flags fields nobody writes alongside fields with no references.
If records hold values you may need, yes. Decide on the data first, because rollback cannot restore it.
13Keep exploring
Connect your Salesforce org. Run your first health scan. Ask your first question. See what you've been missing.