Everything you need, built in.
The essentials for teams that want to move fast without giving up control.
Nine ways deals die. Atlas watches all of them.
Champion silence. Sudden stakeholder turnover. A competitor named for the first time. Price ask creeping up. Meeting cadence collapsing. Procurement process taking 2× longer than similar deals. Each one is a model, each one fires its own alert.
- Champion silence (absolute and relative to baseline)
- Stakeholder turnover (LinkedIn job-change monitoring)
- Competitor mentions (new vs. already-in-set)
- Discount drift > 2σ from comparable won deals
An alert is only useful with a move attached.
Every anomaly comes with 3 suggested plays — specific, contextual, and drawn from plays that worked on similar at-risk deals in your history. Not generic advice. Actual 'send this, call this person, escalate here.'
- 3 recommended moves per alert, ranked by historical lift
- Auto-draft Slack message, email, or calendar invite
- Manager escalation on high-severity anomalies
- Play outcomes tracked to improve recommendation quality
Measurable impact, not hypotheticals.
Atlas tracks rescue rate: the percentage of at-risk deals that return to healthy status after a save play runs. Customers see 38-54% rescue on anomaly-detected deals, vs. 12-18% on undetected risks.
- Pre/post rescue rate tracked per play
- Dollar value of deals saved quantified per quarter
- Rescue rate per rep · coaching signal for managers
- Executive briefing: at-risk volume and save ratio
Teams ship revenue with this.
Real-world use cases across every revenue function.
Frequently asked questions
How is this different from deal health scores?
Health scores are continuous (0-100). Anomaly detection is event-driven: it fires when something specific changes — a champion stops replying, a new competitor appears. Complementary, not duplicative.
Won't I get alert fatigue?
Severity tiers (low/medium/high), alert budget per rep per day, and per-team quiet hours. Tune what wakes you up.
What if the model is wrong?
Every alert has a 'not actually risky' button. Feedback flows back to the model. False-positive rate shown in settings (typical: 6-9%).