A controlled path to cleaner records
Record matching
Compare internal names, professional identifiers, firms and locations with normalized SIE Atlas attributes. Match rules and review thresholds can reflect your input quality.
Firm normalization
Bring variant firm names toward a consistent account structure while preserving relevant firm relationships and avoiding unsupported assumptions.
Category alignment
Translate inconsistent internal labels into current Canadian registration-category context where a source supports the relationship.
Defined-field enrichment
Append agreed business location, contact, source-date or historical fields where available, permitted and supported. Output can be scoped to operational need.
Worked example: benchmarking a legacy CRM
A distribution team submits an approved subset containing names, firms and business locations. SIE Atlas compares it with normalized professional and firm records, returns match indicators and proposed category mappings, and separates uncertain cases. The customer reviews changes before import and uses regulator tools for authoritative checks where needed.
CRM enrichment FAQs
Do you overwrite our source CRM?
No. A benchmark or enrichment output can be reviewed before your team decides how to update internal systems.
How are uncertain matches handled?
Matching can use identifiers and combinations of name, firm and location. Ambiguous records should be flagged for review rather than forced.
Can contacts be appended?
Business contact fields may be appended where available, permitted and included in the agreed output.
Will every input row match?
No. Match rates depend on input quality, population overlap and available identifiers.
Can you normalize registration categories?
Yes, where source context supports the mapping; authoritative status should still be checked with the appropriate regulator.