AI systems that help you stop churn.
Custom AI for growth-stage and scaling SaaS companies — customer health scoring, support automation, onboarding activation, and RevOps intelligence. Built on your stack. Full source code ownership.
The friction
Where your SaaS ops are breaking right now
Churn signals visible too late to act
Standard health scoring based on logins misses the real leading indicators. By the time NRR starts moving, the decision was made weeks ago.
Support tickets that don't need a human
Most B2B SaaS tier-1 volume is automatable. You're paying $12–18 per ticket for questions that a well-trained AI resolves in 8 seconds.
Signups that never activate
1 in 3 new signups churn in the first 30 days without completing onboarding. Manual outreach misses the intervention window by days.
CRM data that sales ops spends Fridays cleaning
Deal stages, contact info, and activity logs lag reality by weeks. Forecast accuracy is a function of who updated Salesforce last, not what's actually true.
Product analytics that require the data team
Every ad hoc product question goes into a data team queue. By the time the answer comes back, the meeting that needed it has already happened.
Feedback you can't synthesize at scale
NPS responses, support tickets, sales call transcripts, and Slack messages contain the product roadmap. But nobody has time to read 4,000 data points per quarter.
Diagnosis
Where your ops break — and what fixes it
Four operational failure modes. Four AI systems that remove them.
Churn signals you see too late
Your customers decide to cancel 45 days before they actually do. Health scoring based on login frequency misses the real signals: feature abandonment, support ticket sentiment, integration disconnections.
Input: product events, support tickets, NPS scoresOutput: health score 0–100 + churn probabilityAlert: Slack/CRM when score drops below thresholdAction: auto-route to CSM for intervention
Support tickets that don't need a human
68% of your B2B SaaS support volume is tier-1: how-to questions, billing lookups, feature requests. Every one of those handled by a human is $12–18 in cost that competes with your CAC.
Input: ticket text, user tier, product contextOutput: resolution or escalation with reasoningCoverage: 60-70% of tier-1 volumeIntegration: Intercom, Zendesk, Linear
Users churning in the first 30 days
30% of your signups never complete onboarding. Each one represents $400–$2,000 in CAC that you'll never recover. Manual outreach scales poorly and misses the right intervention window.
Trigger: user completes step N, not step N+1Action: personalized in-app message + emailEscalation: CSM alert after 48h no activationResult: activation rate up 40%+
Pipeline data that needs a human to make sense of
Your CRM is 40% stale entries. Deal stages rely on rep memory, not product signals. Forecast accuracy depends on who updated Salesforce last week.
Input: CRM data, product usage, email signalsOutput: deal health score + pipeline forecastAuto: CRM field updates from product eventsReport: weekly RevOps digest to Slack
Architecture
The SaaS Operating Layer
Three layers of intelligence that sit on top of your existing tools and make your SaaS company run like a larger team.
Customer Intelligence Layer
- Health scoring + churn prediction
- NPS correlation and trend analysis
- CSM escalation automation
Operations Intelligence Layer
- Support tier-1 automation
- RevOps CRM hygiene + forecasting
- Onboarding activation triggers
Product Intelligence Layer
- Feature request theme clustering
- Sales call signal synthesis
- Roadmap priority scoring
What we deploy
Six systems. One SaaS company on AI.
Each system is production-deployed, not a proof of concept. Built on your existing stack. Full source code at close.
Case study
Results from a real deployment
B2B SaaS company reduces churn 34% and automates 60% of support in 11 weeks
A growth-stage B2B SaaS company with 800 accounts was seeing churn accelerate. Health scoring was login-based and wrong. Support was 3 FTEs handling 2,400 tickets/month. Product feedback was unstructured across 6 channels.
What we built
- Customer health engine ingesting product events, support sentiment, and NPS across 800 accounts
- Support AI resolving 60% of tier-1 tickets with full context in Intercom
- Activation flow triggered by user behavior signals — 40% improvement in 30-day activation
- Product signal synthesis feeding weekly roadmap briefs to PM team from 4 data sources
Alex T., Head of Customer Success
Growth-Stage B2B SaaS
Integrations
Connects to your existing stack
We build on top of what you already run. Nothing gets replaced.
Product & Analytics
CRM & RevOps
Support
Data & Workflow
FAQ
Questions technical teams ask
Ready to start
Book a 30-minute discovery call.
We'll map your highest-leverage systems.
No pitch deck. We'll audit your current SaaS operations, identify the exact automations worth building — churn, support, onboarding, RevOps — and give you a scope with ROI projections before you commit.
Book discovery callTypical first response within 4 business hours.