Audits your CRM export for duplicate contacts and companies, stale open deals, and missing pipeline stage data, then scores overall data completeness. A second phase turns that clean pipeline into a weighted forecast: best/likely/worst case, commit vs upside, and gap-to-quota. Account scoring and outbound activation close the remaining phases of the sequence.
Forecasts built on a messy pipeline are really just guesses with a spreadsheet attached.
Phase 1: CRM Data Audit
A synthetic CRM export seeded with realistic messy data: 12 contacts, 11 companies, 10 deals.
93.3/100
Completeness score
5
Duplicate clusters found
5
Stale deals flagged
Zero false positives on the genuinely distinct records in the same test set.
Phase 4: Pipeline Forecast
10 deals scored against a $300K quarterly quota.
$262K
Best case
$173.2K
Likely case (weighted)
0.85x
Coverage ratio
Every number reconciles: best case, likely case, and worst case all tie back to the same underlying deal list.
The audit phase reports and flags; a client's team or Telemeter Strategy handles the actual fixes.
Deal stage, activity recency, and historical close patterns from the same CRM, not a flat probability by stage.
Runs against your CRM using your own credentials, through your own AI instance. We don't copy, store, or retain your data.