Revenue Intelligence

Stop explaining why the number was wrong

Scalivo connects your CRM activity, product usage, and billing data into one model. Quota attainment by rep, by segment — with confidence intervals that hold up in CFO reviews.

±4.2% Median forecast error, 90-day window
3 data streams CRM · product usage · billing — merged in one model
< 48 hrs Median time to first forecast after connecting stack
28+ Integrations across CRM, PLG tools, and billing

Your CRM only shows what reps remember to log

Product usage tells you which accounts are going dark — but that signal lives in Mixpanel or Amplitude. Billing tells you who's contracting — but that's in Stripe. Your weekly commit call is still a judgment call averaging three dashboards open in separate tabs. Forecast category stays "best-case" until it's "closed-lost." We built Scalivo because this is how bad forecasts happen — not from bad reps, but from signal fragmentation.

Without a unified model
  • Forecast category set by rep conviction, not signal weight
  • Churn risk visible in product data 6 weeks before anyone acts
  • Expansion ARR left at renewal because CS never got the engagement signal
With Scalivo
  • Model-assigned close probability from CRM + product + billing daily
  • Churn early warning fires 60–90 days before renewal, traceable to signal
  • Expansion candidates ranked by engagement velocity and billing headroom

Three streams. One model. One number.

01

Connect your stack

Salesforce or HubSpot for pipeline. Mixpanel, Amplitude, or Segment for product signals. Stripe or Chargebee for billing. No ETL required — native connectors, data flowing in hours.

02

Model builds automatically

Scalivo trains a deal-outcome model on your historical data — weighting signals by what actually predicted closed-won at YOUR company, not industry averages.

03

Forecast by rep, segment, and account

Pull up quota attainment projections with confidence bands. Drill from segment to deal. Flag the accounts the model thinks your reps are over-confident on.

Four modules. One model trained on your data. Not a shared template.

Expansion Engine

Surface expansion ARR before the renewal window closes

Scalivo ranks accounts by expansion probability — combining product engagement velocity, current contract value, and days to renewal. Your CS team gets a prioritized list, not a spreadsheet to sort. Accounts with high DAU/MAU growth and billing headroom float to the top. The ones your team would have left at flat renewal.

See Expansion Engine

Rep attainment accuracy scores

Track which reps consistently over-commit and which under-commit against their forecast category. Adjust the model's rep-level weight, then coach from data — not from the pipeline review gut-check.

Churn risk with signal traceback

When a churn risk flag fires, Scalivo shows the exact signals that drove it — login frequency change, feature abandonment rate, support ticket volume. Not a black-box health score. Every flag is explainable in a CS call.

P10/P50/P90 confidence intervals

Every forecast outputs a range, not a single number. Present your P50 to the board and your P10 to the CFO — with the model's week-over-week version history so you can show the forecast held.

Signals where your team already works

Weekly digest to your RevOps Slack channel. Risk flags and expansion scores write back to Salesforce or HubSpot opportunity fields. No new dashboard to check — the signal comes to you.

Your stack, not ours

28 connectors. No ETL required. Data flowing in hours.

Native read-only OAuth connections to Salesforce, HubSpot, Mixpanel, Amplitude, Stripe, Chargebee, Snowflake, BigQuery, and 20 more. Scalivo does not require a data engineer to set up and does not write to source systems unless you configure it to.

See all 28 integrations
Salesforce
HubSpot
Mixpanel
Amplitude
Stripe
Snowflake
Slack
Segment
Chargebee
BigQuery

What CROs and RevOps leads say after 90 days

"Forecast error went from ±28% to ±6% in one quarter. The board stopped asking 'why was the number different.' We just show the P10/P50/P90 band now and the conversation moves on."

Sarah Voss
VP Revenue · B2B SaaS · HR tech · ~$45M ARR

"We identified three expansion candidates the CS team had written off as flat renewals. The product engagement signal was there — we just weren't looking at it alongside billing headroom."

Marcus Ikeda
Head of Customer Success · B2B SaaS platform · ~$28M ARR

"We were quoted 60-day implementations by two other vendors. Scalivo was two days. The signal model was running before I'd finished writing the onboarding recap email."

Priya Mathur
RevOps Lead · B2B marketplace · $18M ARR

Connect your stack. Get a forecast worth committing to.

14-day free trial. No credit card. First forecast within 48 hours of connecting your CRM.