Aformity

Audit trail for every data decision.

See who changed mappings, approved fixes, updated templates, and moved customer data toward import.

Keep launch decisions inspectable

Aformity keeps operational history readable for implementation, support, security, and procurement reviews.

Track changes across the project

Capture mapping edits, validation outcomes, customer responses, and approval events as the project moves forward.

App / Audit

Activity log

Preview

Launch history

09:14 Customer uploaded accounts.csv Client admin
10:42 Mapping changed for owner_email Implementation
11:06 Validation rule accepted Aformity AI
12:18 Output approved Ops lead

Tie decisions back to source data

Review which rows changed, why they changed, and which rule or person approved the result before import.

App / Source / Transform

Source transformation

Preview

Transformation rules

AI suggestions stay attached to source fields.

2 to review
company_name Account.name trim + title case Accepted
owner_email Team.owner match user by email Review
plan_start Contract.starts_at parse date Accepted
legacy_id External reference preserve Queued
4 mappings accepted
1 owner needed
2 reusable rules

Support handoffs after launch

When questions come up later, teams can inspect the final path from original upload to import-ready output.

App / Replay

Replay run

Preview

Run 044 comparison

Re-run the same preparation path against the revised file.

StagePreviousCurrentDiff
Source file 1,284 rows 1,286 rows +2
Transform 5 functions 5 functions same
Validate 0 blockers 2 blockers +2
Output Locked Queued hold

Audit trail FAQs

Answers for teams that need clear records of how customer data became import-ready.

An import audit trail tracks uploads, mapping edits, validation outcomes, customer responses, cleanup decisions, approval events, and final outputs so teams can inspect how customer data moved from source file to launch handoff.

Launch teams often need to explain why a field changed, who approved a fix, which rows were held back, and what rules shaped the output. An audit trail keeps those answers connected to the original data.

Yes. When support, security, or customer success teams need context after go-live, the audit trail helps them review the path from original upload to import-ready data.

No. Regulated teams benefit from stronger evidence, but any team handling high-stakes customer imports can use an audit trail to reduce ambiguity, rework, and launch risk.

Make launch history visible.

Keep every customer data decision connected to the work that produced it.

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