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AI · Deal Prediction

Know which deals will close. Before your rep does.

A live 0-100 win probability on every deal, trained on 2M+ closed-won and closed-lost outcomes. Stage signals, engagement velocity, decision-maker activity, and 40+ other features — updated every 15 minutes.

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Pipeline win probability
Q2 · 134 deals · refined 4m ago
Stripe · Negotiation · $128K
92%
Acme Corp · Proposal · $96K
81%
Figma · Demo · $78K
67%
Linear · Discovery · $64K
54%
Vercel · Qualification · $42K
28%

Everything you need, built in.

The essentials for teams that want to move fast without giving up control.

Gradient-boosted model
Trained on 2M+ outcomes across 14 verticals. Outperforms rep self-scoring by 3.1×.
±4% MAE
Mean absolute error benchmarked against actual close outcomes, retrained every 14 days.
Explainable by design
Every score shows top 5 drivers (stage, last touch, champion activity) — no black box.
Refresh every 15 min
Scores re-compute on email replies, meeting outcomes, and stage changes — not nightly batches.
Model inputs

40+ signals, weighed against 2M outcomes.

Stage-in-pipeline, days since last touch, meeting cadence, decision-maker engagement, champion response times, discount discussions, and 34 more features go into every score. Every input is auditable.

  • Temporal features: stage velocity, days-in-stage, forecast drift
  • Engagement: reply rate, thread depth, meeting attendance
  • Stakeholder: champions identified, exec threads, mobilizers
  • Commercial: pricing discussions, procurement signals, legal back-and-forth
Why Stripe = 92%
Top drivers · click to audit
Champion replied in < 2h · last 7 days
+18
MSA redlined by vendor legal
+14
Decision-maker in last meeting
+11
Pricing questions resolved
+9
No discount ask > 15%
+6
Forecast roll-up

Better forecasts, one deal at a time.

Per-deal probabilities aggregate into team, region, and company forecasts. Reps submit commit / best-case; Atlas produces the third number — the one that's right ±3% at quarter-end.

  • Deal-level → rep-level → team-level → company-level roll-up
  • Variance explained in plain English ('Q2 weaker: Stripe slipped')
  • Submit AI Forecast as a first-class forecast category
  • Historical accuracy shown per rep and per quarter
Q2 Revenue roll-up
Company level
Committed
$3.2M
Best Case
$5.1M
AI Forecast
$4.4M
Quota
$4.2M
Alerts & interventions

Scores that change, move money.

When a deal slips from 72% to 48% overnight, Atlas fires a Slack alert with the exact reason and a suggested play. Leadership sees the at-risk deals before the weekly pipe review.

  • Slack / Teams / email alerts on 10+ point drops
  • Auto-generated save play with 3 suggested actions
  • Deal-room summary for exec intervention
  • Weekly 'at-risk' digest for managers and VPs
Risk alert · Linear
Score fell 74 → 42 overnight
Champion silent · 11 days
Risk
Second competitor identified
Risk
Suggested play: exec-to-exec intro
Act
Assigned to: Alex M.
Owner

Teams ship revenue with this.

Real-world use cases across every revenue function.

AEs prioritizing their book
Work the 72%+ deals first. Don't waste Friday afternoon on the 19% 'pipeline filler' that's been stale since February.
Sales leaders running pipe reviews
Sort by probability, not by rep mood. Discuss the deals where the model and the rep disagree — that's where coaching happens.
RevOps building accurate forecasts
Stop relying on rep-submitted probabilities that drift 22 points quarter-over-quarter. AI Forecast is +/- 3.2%.
Finance planning the quarter
AI forecast feeds directly into your planning model. Commit, Best Case, and AI side-by-side in a single CSV export.

Frequently asked questions

How accurate is the model?

±4% mean absolute error against actual close outcomes across our customer base, measured over trailing 90 days. Accuracy varies by vertical and stage — Atlas shows per-stage MAE in settings.

Is it trained on my data or shared data?

We ship a general base model trained on de-identified industry data. You can opt into customer-specific fine-tuning that uses only your data, deployed in an isolated tenant. No training across customers, ever.

Can reps override the AI score?

Yes. Reps can enter their own probability alongside the AI score. Managers see both and can require a reason when they diverge by 20+ points.

How often does it refresh?

Every 15 minutes for active deals, real-time on stage changes or email replies. Closed-won and closed-lost freeze at close date.

Keep exploring
Forecasting →Opportunity scoring →Pipeline →Analytics →For sales teams →

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