Does ax1om use third-party data?

No. ax1om trains exclusively on your own CRM data. No external enrichment, no third-party signals, no data from other customers.

How is ax1om different from MadKudu or 6sense?

MadKudu and 6sense use third-party intent data and industry benchmarks. ax1om uses only your Salesforce or HubSpot pipeline history, which means scores reflect your actual customers, not industry averages.

Do I need a data science team to use ax1om?

No. ax1om handles the entire ML pipeline (model training, scoring, CRM writeback, and weekly rescoring) without any code or data science expertise required.

Why don't sales reps trust lead scores?

Most scoring tools produce a single number with no explanation. ax1om includes SHAP values with every score showing exactly which CRM fields drove each prediction, so reps understand and trust what they see.

Revenue intelligence Beta

Clarity for every conversion decision.

A predictive scoring model trained on your own pipeline, not industry benchmarks. Every score comes with a SHAP explanation so your reps know exactly which CRM fields drove it.

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Trained on the data you already have · SHAP explainability on every score

Model dashboard

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.

ax1om model performance dashboard showing AUC-ROC 0.8026, 3.14x lift at top 20%, 36.7% precision, lift curve by decile, score distribution histogram, and feature analysis table with SHAP impact and Feature Stability Score columns — Trained on the public UCI Bank Marketing dataset · 36,168 records · 53 features · 88 seconds

Explainability

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.

Feature analysis table showing SHAP impact, splits, Feature Stability Score, and expandable field-level breakdowns for Industry, Title, LeadSource, and NumberOfEmployees — SHAP feature importances with per-value breakdowns and Feature Stability Scores

Key insights panel showing natural language findings: VP Sales titles convert 2.6x higher, VP titles convert 2.4x higher, revenue titles convert 2.3x higher — Natural language insights derived from the trained model

01 / How it works

Three steps to scores your reps actually trust.

Step 01

Connect your CRM

Secure OAuth connection to Salesforce, HubSpot, or upload CSVs. ax1om never stores CRM credentials.

Step 02

Train on your pipeline

ax1om trains a dedicated model on your closed-won and lost history. No cross-customer data, no shared models.

Step 03

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.

Google Cloud

SOC 2 Type II · ISO 27001 · ISO 27018
Supabase

SOC 2 Type II
Vercel

SOC 2 Type II · ISO 27001
Cloudflare

SOC 2 Type II · ISO 27001
Stripe

SOC 2 Type II · PCI DSS L1
Sentry

SOC 2 Type II

ax1om compliance

SOC 2 Type II Audit Q4 2026
GDPR DPA with SCCs available
CCPA Compliant as service provider
US data residency GCP us-central1 only

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Ready to see your own pipeline, not someone else's benchmark?

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