For Revenue

Stop Leaving Money
on the Table

Your sales team has millions in opportunity hidden in messy Salesforce notes. One BD writes "rev," another writes "revenue," a third writes "turnover." Someone mentions a company hit their target revenue (a signal they're ready to sell), but it's buried in a six-month-old note. Meanwhile, companies with clear buying signals slip through because no one connected the dots. Preql's AI agents turn unstructured CRM data into actionable revenue intelligence.
The Executive Intelligence Gap

  • Valuable signals buried in unstructured notes. BDs write notes inconsistently. "Hired banker" or "owner retiring" are clear buying signals, but they're lost in thousands of account records.

  • Turnover kills deal momentum. When BDs leave, their tribal knowledge disappears. Deals that were warm six months ago go cold.

  • Too many reps looking at too few accounts. Without AI-powered prioritization, your team wastes time on low-probability opportunities while high-intent buyers go untouched.

AI That Finds Hidden Deals

Preql standardizes and structures your CRM data automatically, identifying deal signals and prioritizing accounts based on propensity to buy.

  • Extract signals from messy notes. Our AI agents understand context, identifying buying signals even when they're written inconsistently across thousands of account records.

  • Prioritize high-intent accounts automatically. Rank opportunities by likelihood to close and deal size, so reps focus on the accounts that actually matter.

  • Preserve institutional knowledge. When BDs turn over, their insights remain structured and accessible to whoever takes over the accounts.

Use Cases

Deal Signal Detection

With 200,000+ software companies in Salesforce and 700 BDs writing notes differently, teams are missing $100M+ in deals annually. Preql agents identify buying signals like "hired banker," "looking to retire," "reached revenue target," even when written inconsistently, ensuring no opportunity slips through.

Account Prioritization & Scoring

Stop wasting time on low-probability accounts. Preql analyzes all account data, including: notes, engagement history, company signals etc, to rank accounts by propensity to buy, deal size, and timeline. Your team focuses on the 20% that drives 80% of revenue.

Pipeline Forecasting Accuracy

Improve forecast accuracy by analyzing historical patterns in your CRM notes. Understand which signals actually correlate with closed deals, and build predictive models that tell you which opportunities will really close this quarter.

Post-Turnover Deal Recovery

When a top BD leaves, their replacement inherits messy notes and incomplete context. Preql structures all historical interactions, extracts key insights, and provides the new rep with a complete view of every account's history and status.

Frequently Asked Questions

What does Preql actually do?
How is Preql different from ETL or data prep tools?
What teams does Preql work with?
Is Preql AI enterprise-ready?
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