Find likely duplicate records with stated match rules and evidence, for a person to merge.
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Use this for contacts, leads, or accounts from a dated export.
Write the rules before matching, for example exact email, same domain and surname, or same company name after removing "Ltd" and "Inc". Give each rule a strength: strong, likely, or weak. Record the export date and row count the rules ran against.
For each pair or group show:
Keep groups with open deals or different owners apart; they need a person to look first.
Return three lists: strong matches ready for review, likely matches that need a check, and pairs you ruled out. Give counts for each. Say which reports will change once the merges are done.
Never merge, delete, or edit a record yourself, and do not guess which value is correct when two records disagree. A person approves and makes each merge.
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Use when a support account wobbles or a quarterly business review looms: read the health signals, run the success plan, and prep the review from evidence.
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Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.
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Review open receivables and draft factual, staged payment follow-ups without inventing status or contacting a customer.
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Write ad variants that each test one idea, within platform limits and supported claims.
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Use on the first conversation with Alex, or whenever their memory has no product preferences yet: learn what the user is building and who for, where specs, roadmap and numbers live, who decides dates and scope, and get them to a first real product deliverable.
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Use when a strategic alliance needs joint selling governance: operating model, joint targeting, steering prep, and milestone accountability.
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