Clarity for every conversion decision.
Prescriptive scoring trained on your pipeline, not industry benchmarks. Every score tells your reps which accounts to prioritize, when to engage, and why.
Right company · Right person · Right time, answered separately
A real model. A public dataset. Honest numbers.
The UCI Bank Marketing dataset is a standard public ML benchmark. 36,168 records, 11.7% baseline conversion rate. Here's what ax1om trained on it in 88 seconds: 0.80 AUC, 3.14x lift on the top decile, and a Feature Stability Score on every field so you know which signals hold up when the model retrains.
Every score comes with a reason.
SHAP feature importances on every field, Feature Stability Scores that tell you which signals survive retraining, and natural language insights that translate model output into operator decisions.
Most scoring tools collapse three different questions into one number.
ax1om answers them separately.
Right company
ICP fit score at the account level. Which companies match the profile of your best customers?
Right person
Contact prioritization. Within a qualified account, which individuals are worth your team's time?
Right time
In-market timing. Is this account showing signals that they're ready to buy now, or should you wait?
Three steps to scores your reps actually trust.
Connect your CRM
Secure OAuth connection to Salesforce, HubSpot, or upload CSVs. ax1om never stores CRM credentials.
Train on your pipeline
ax1om trains a dedicated model on your closed-won and lost history. No cross-customer data, no shared models.
Write scores back to CRM
Predictions and explanations land directly on Lead and Account records. SHAP values show exactly why.
Backed by enterprise-grade infrastructure
ax1om runs on providers that hold independent SOC 2 Type II, ISO 27001, ISO 27018, and PCI DSS Level 1 certifications. Our own SOC 2 Type II audit begins Q4 2026.
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Google CloudSOC 2 Type II · ISO 27001 · ISO 27018 -
SupabaseSOC 2 Type II -
VercelSOC 2 Type II · ISO 27001 -
CloudflareSOC 2 Type II · ISO 27001 -
StripeSOC 2 Type II · PCI DSS L1 -
SentrySOC 2 Type II
- SOC 2 Type II Audit Q4 2026
- GDPR DPA with SCCs available
- CCPA Compliant as service provider
- US data residency GCP us-central1 only
What teams ask before they start.
We already have Einstein / HubSpot scoring.
Those tools are trained on general patterns across their entire customer base, not on your closed-won outcomes. ax1om trains on your history, so the score reflects your conversion patterns, not an industry average.
We're not big enough for this.
ax1om is specifically built for Series A-C companies. The guided setup works with as few as 50 closed-won opportunities using TabPFN. You don't need years of CRM history, and the model improves as your data grows.
Our RevOps team doesn't have data science resources.
That's the point. ax1om handles the entire ML pipeline: feature engineering, model training, scoring, CRM writeback, and weekly retraining. No code, no notebooks, no data science expertise required.
How is this different from a spreadsheet scoring model?
A spreadsheet model uses weights someone guessed. ax1om uses weights the data determined, specifically your closed-won outcomes. The difference shows up in the accounts that surprise you: the ones that score high because they match a pattern your team never articulated.