Your MRR looks healthy. Something is quietly wrong.

Incremenza was built by Alejandro Martinez, who spent years inside large-scale technology companies before leaving to consult for small SaaS companies. The same problem came up every time: founders had data everywhere but couldn't see which customers were actually making them money, which were quietly contracting, or which channels were delivering customers who stayed. He couldn't scale himself as a consultant, so he built the system that does what he'd do, with his diagnostic frameworks and playbooks baked in. This is not a generic analytics tool built by engineers who've never run a business. It's a consultant's method, productized for founders who need it at 11pm on a Tuesday.

Those tools are built for $5M+ ARR SaaS companies with dedicated customer success teams. Their pricing reflects that: typically $20,000 to $60,000 per year. Incremenza is built for bootstrapped and early-stage subscription businesses where the founder is often the customer success lead. You get the metrics that matter: health scoring, cohort analysis, NRR (net revenue retention), plus the financial intelligence and operating rhythm those tools do not include, all for $149/month. When you grow past 1,000 customers and need a dedicated team with deep playbook automation, those tools are the right next step. Until then, Incremenza is what you actually need.

AI tools that connect to your existing software are good at answering one-off questions: pull last month's revenue, summarise an invoice, flag an overdue payment. They read your data on demand and respond. For quick tasks, that works. Incremenza does something different. It stores your transaction and customer data, calculates health scores for every customer, tracks cohort retention curves, monitors NRR and contraction revenue continuously, and detects when something has changed, before you ask. The churn signal that appears in a customer's health score three months before they cancel is only visible because the system has been tracking that customer's payment behaviour, MRR trend, and support patterns over time. One sees a snapshot. Incremenza sees a trend. For a subscription business, the difference between a snapshot and a trend is the difference between knowing a customer cancelled and knowing one was about to.

Not directly today, and we made that choice deliberately. Most bootstrapped SaaS companies do not have product analytics fully wired up, and even when they do, financial signals: payment behavior, contract changes, support patterns, predict churn earlier and more accurately than usage signals at this stage. We focus on what your billing data already tells us, plus custom health signals you can update manually. If product analytics becomes critical for your workflow, that is typically a sign you are scaling beyond our ideal fit, and we will point you toward the right next tool.

Health scores combine three signal types: payment behavior (on-time payments, failed payments, downgrades), engagement (login frequency, feature usage where measurable, last login), and support (ticket volume, sentiment if available). The score is a 0-100 composite that updates automatically as your data changes. You can adjust signal weights to match how your business defines "healthy."

Yes. The cash flow forecast includes MRR projections for the next 30, 60, and 90 days based on your current customer base, expected renewals, churn risk, and pipeline. Each month shows a confidence range, wider for further-out months. Renewal forecasts specifically show which customers come up for renewal and total MRR at stake.

Yes. Incremenza connects directly to Stripe for billing data, and to your support tool through Zapier or direct integrations. Both feed into the customer health scoring automatically. The integration setup is one-time. Once connected, data flows continuously.