Free CRM data tool

Inspect the sample before you trust the system.

Review a small CSV for missing values, duplicate records, inconsistent formats, and fields that may not support the workflow your team expects.

Review a CSV sample

How it works

A clean import can still support a broken workflow.

The sampler profiles each column, finds exact duplicate rows, and flags observable inconsistencies. Every finding includes the rule that triggered it.

It does not connect to your CRM, infer business meaning, repair records, or approve a migration. A sample can expose risks; it cannot prove the full dataset is healthy.

Review the sample

Use the smallest safe dataset.

Remove names, email addresses, phone numbers, account identifiers, payment details, health information, secrets, and confidential or regulated data. Synthetic or deliberately anonymized records are safest.

Your data-health snapshot

CRM sample

Sample snapshot

What the sampler reviewed

Rows
Columns
Findings
Duplicate rows

Priority findings

Signals to inspect before relying on the data

Column profiles

What is observable in each field

Column names, filled and missing values, distinct values, likely formats, and review notes
Field	Filled	Missing	Distinct	Likely format	Review note

Duplicate evidence

Exact repeated rows

Workflow review

Questions the sample cannot answer alone

What it inspects

Four visible data risks.

01
Completeness Which fields are often blank?
02
Duplication Which rows repeat exactly?
03
Consistency Which fields mix formats or casing?
04
Workflow fit Which fields need ownership or business-rule review?

Search Cadence Lab

When AI creates more work for the people using it