The AI that knows which customers are leaving — 60 days before they do.
HelmAI watches every signal. You'll know who to call, and why, while there's still time.

Three layers. One number that tells you who's leaving.
A calm dashboard. A loud signal. Nothing else to learn.
Plans for individuals and teams.
- Single user, single workspace
- Daily Watchlist
- +15 integrations
- Email support
- Up to 20 team members
- Unlimited integrations
- API & MCP access
- SSO
How AI reduces customer churn.
How do I reduce customer churn?
The most effective way to reduce churn is to identify accounts at risk 30 to 60 days before they cancel — and intervene with the right person, on the right issue, through the right channel. That means continuously monitoring usage, sentiment, support, and billing signals together, rather than relying on quarterly reviews. HelmAI automates that monitoring across your stack and surfaces a daily Watchlist of which accounts to call and why.
Can AI predict customer churn before it happens?
Yes. Modern churn-prediction models learn from your historical retained vs. churned accounts and identify the leading indicators specific to your business. The strongest signals usually appear weeks before a cancellation — drops in active usage, longer support cycles, billing friction, sentiment shifts in conversations. HelmAI builds a model on your own retention history and flags drifting accounts up to 60 days before they cancel.
What signals predict customer churn?
The most reliable signals are usage decay (logins, key actions, seats activated), support patterns (rising volume, slower replies, escalations), billing friction (failed cards, downgrade requests), and sentiment shifts across calls, email, and Slack. No single signal is enough on its own. HelmAI combines them into one risk score per account and explains which three signals triggered each flag.
How accurate is AI churn prediction?
Accuracy depends on data quality and how many systems are connected. With usage, billing, support, and conversational data wired in, top-of-funnel precision typically lands in the 70–85% range — meaning roughly three of every four flagged accounts are genuinely at risk. HelmAI publishes per-customer precision and recall so you can audit exactly how often it is right.
When should my CS team intervene with an at-risk account?
As soon as the risk score crosses the high-risk threshold — typically 45 to 60 days before predicted cancellation. Earlier intervention gives the team time to fix the actual underlying issue (a stalled integration, a champion change, a billing dispute) rather than scrambling during the renewal call. HelmAI tells you who to call, what changed, and what to say in the first message.
What is the best churn-prediction software for SaaS?
The right tool depends on team size, ARR, and where your customer data lives. Look for software that connects to all four signal sources (CRM, billing, product analytics, conversations) without requiring a data warehouse, explains why each account is flagged, and pushes actions into the tools your CS team already uses. HelmAI was built for Series A through Series C B2B SaaS teams — see pricing above or book a demo.
Steady the wheel.
We'll show you which accounts are leaving — and let you decide if we're right.