Delpha scores Salesforce account, contact and opportunity data across six quality dimensions and corrects duplicates and bad values with AI recommendations.
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Calculate a Quality Score for accounts, contacts and opportunities across completeness, validity, uniqueness, consistency, accuracy and timeliness
Track data quality over time and navigate dimensions to filter records needing correction
Categories: Data Quality
Accept or reject recommended values with a single click as a data steward
Apply automatic corrections or let end users correct records through the Co-Pilot conversation
Categories: Data Quality
Detect duplicate accounts, contacts and leads with machine-learning matching and an AI duplicate-likelihood score
Configure detection rules and monitor Salesforce continuously for new duplicates
Categories: Data Quality
Check account and contact fields such as legal ID, address, website, phone and email against six quality dimensions
Provide recommended values with a confidence score
Categories: Data Quality
Define merge rules that prioritize fields or apply custom field operations
Merge automatically above a confidence threshold, by mass merge, or after manual review
Review an audit trail of merged and unmerged records
Categories: Data Quality
Use machine-learning algorithms to detect subtle duplicates and score duplicate likelihood
Generate AI recommendations with confidence scores for data corrections
Categories: Artificial Intelligence
Guide sales, marketing and customer success users through record corrections in the Delpha Co-Pilot / Assistant Bot conversation
Categories: Artificial Intelligence
Automate merging of matched duplicates above a configured confidence threshold
Apply automatic data correction and schedule record refresh frequency
Categories: Artificial Intelligence
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