Pacer AI helps Sales Leaders
make plan with confidence.

Bottom-up sales forecasting builds the number from booked revenue and open pipeline at the account, product and rep, then reconciles it to Finance. Pacer AI is that agent for sales leaders. It shows pace to plan by market, segment and rep, names the gap, and updates in real time, inside Claude.

Pace to plan compares booked ARR with the plan prorated to today. If the FY plan takes ARR from $100M to $120M, by September 20 the plan to date is about $114.4M; booked ARR of $112.2M means you are $2.2M behind plan. Pacer AI reports this for the month, quarter and year, with the forecast landing: booked ARR plus weighted open pipeline.

Type “gap” in Claude. Pacer AI sizes the gap still to close (the target minus booked ARR minus weighted open pipeline) and lists the two motions that can close it: expansion white space at accounts renewing soon, meaning what each could still buy across your products, and new-logo prospects, with warm ones first where a past champion now works.

Pacer AI is built for CROs, VP Sales, RevOps and CFOs at B2B companies with complex GTM motions and $10M or more in recurring revenue.

Most engagements go from kickoff to board-ready output in days, not months. The data cube build typically takes 2–4 weeks depending on source system complexity.

CRM (Salesforce, HubSpot), billing (Stripe, Zuora, Chargebee), ERP (NetSuite, Sage Intacct), and data warehouses (Snowflake, Databricks, BigQuery).

FP&A tools start with the GL. We start with transactional customer data to build M&A-grade ARR decomposition, cohort retention, and expansion analytics that FP&A tools cannot produce.

Yes. We work with operating partners and deal teams on both pre-close diligence and post-close value creation across the portfolio.

Ownership sits with RevOps; the definitions sit with Finance. The common failure is a forecast owned by RevOps that never reconciles to Finance’s reported ARR. Pacer AI recommends building the forecast off the same governed data the finance number comes from, so there is one set of definitions and one answer.

CRM and finance ARR numbers don’t match because they measure two different events: the CRM records bookings when a deal closes, while Finance records revenue as it is recognized — net of contraction, churn, and timing. Without a defined bridge between bookings and recognized revenue, both numbers are correct and neither reconciles. Pacer AI builds that bridge at the account-product grain, so pipeline ties to reported ARR to the dollar.

A VP of Revenue Operations owns four things: the revenue forecast and pipeline cadence, the governed revenue KPI set, quota and territory capacity, and the GTM tech stack. Across the RevOps job descriptions we’ve analyzed, all four are owned by a person, not produced by a system — which is why the role turns over.

Both. The agent does the heavy modeling, and every engagement includes founder-led service, done-with-you or done-for-you, so the model is built, reconciled, and defended by a person. After implementation you run your own modeling, planning, forecasting, and reporting — DIY — with a human in the loop whenever you need one: dedicated office hours, Slack support, and ad-hoc meetings.