Most SaaS companies watch customers leave in slow motion. Across six systems. With no playbook for what to do next.
Every part of SaaS revenue has infrastructure protecting it — except the revenue you've already closed. Rivive is building that layer.
I'm not building this because I spotted a gap.
I'm building it because I've lived every side of the failure.
Founder & CEO, Rivive.ai · Senior CS operator, enterprise SaaS · Building in stealth · Full-time upon seed close · hi@rivive.ai
Senior CS operator. 100+ person org. €2M+ accounts. Daily exposure to Gainsight failing — not in a demo, in practice. Three years watching the gap between signal and action cost real revenue.
A large account churned. Three signals existed across three different tools. No playbook existed. Nobody acted. I've been building the answer to that moment ever since.
I'm building Rivive while employed — deliberately. I have financial obligations I take seriously. That's not a lack of conviction — it's the same discipline I'll apply to your capital. Full-time the day this round closes.
I've been on every side of this failure. That's why I'm the one building the fix.
This isn't a market opportunity I spotted. It's a problem I've lived — from the inside.
Three years inside enterprise CS at scale
Senior customer success operator on $2M+ accounts inside a 100+ person organization, with daily exposure to Gainsight failing in practice.
The moment that made this inevitable
A large account churned. Three signals existed in three different tools. No playbook existed. Nobody acted.
The fix I'm building is the one that would have saved that account.
Prediction has existed for 15 years. Churn is still the #1 SaaS problem.
That's not a coincidence. It's proof that prediction alone doesn't work.
Smarter alerts
Gainsight, ChurnZero, Totango, and 15 years of detection investment created more dashboards and more CTAs nobody acts on.
Enforced intervention
The signal-to-action gap still exists. No tool owns it. Rivive closes it.
Prediction without action is just an expensive alert. We don't predict better — we close the loop from signal to enforced intervention.
The CS industry has a data hoarding problem. We're betting against it.
Three years of Gainsight data. Still can't tell a CSM what to do on Monday morning.
More data = better retention
CSMs feed the system instead of saving accounts. Manual health scores are bias masquerading as intelligence.
Right signals + right action = better retention
10% of the right behavioral signals beats 100% of manual CS interpretation.
A cardiologist doesn't watch your heart 24 hours a day. But an ECG does — detecting irregular patterns weeks before a cardiac event, so the doctor knows exactly when to act.
Rivive does the same for customer health. Continuous behavioral monitoring. Precision intervention. Not panic. Not too late.
We don't need clean data. We need behavioral truth.
The signals that predict churn don't live in a CRM. They live in patterns most teams aren't watching — and require zero data entry from your CS team.
Gmail / Outlook
Response latency trends, thread decay, and champion engagement fade.
Stripe / Paddle
Seat utilization trends, payment timing changes, and expansion versus contraction signals.
Product analytics
Login frequency decay, feature adoption depth, and session length over 6 weeks.
Slack
Internal use only. CSM sentiment in team channels — and a signal when sales, support, and CS are all discussing the same account at the same time.
Connect Gmail, Stripe, and your product analytics. Six weeks of history. We show you which accounts are drifting — without your team logging a single thing.
Gainsight's customers are not our beachhead. They're our destination.
Salesforce didn't start by replacing Oracle. They started with the companies Oracle ignored — and then made Oracle irrelevant. Rivive starts with the SaaS companies Gainsight prices out. Then we come for their customers too.
| ARR | $1M–$15M |
|---|---|
| CS team | 1–3 CSMs or founder-led |
| Stack | Gmail + Stripe + product analytics |
| Decision cycle | Days, not quarters |
| Budget reality | Can't afford Gainsight and won't tolerate 6-month setup |
The path in
Enter through the door nobody is guarding, own the philosophy they can't copy, and make the manual-entry model obsolete at every tier.
Rivive isn't a better Gainsight. It's a rejection of what Gainsight is built on.
Competing on features is a losing game. We compete on philosophy — and philosophy can't be sprint-copied.
| Gainsight | Rivive | |
|---|---|---|
| Core bet | More data = better retention | Right signals + right action = better retention |
| Requires | 6–18 months setup, CS behavior change | Gmail + Stripe + product analytics. Live in 48 hours. |
| Signal source | CS interpretation, manual logs | Behavioral data only — no human bias in the health score |
| Output | Dashboard with alerts | Enforced intervention with playbooks that self-improve over time |
The playbooks don't come from a template library. They come from what actually works.
Every intervention Rivive executes becomes training data for the next one. The library compounds with every customer onboarded.
Engineered from discovery: 30+ interviews with VP CS, CRO, and RevOps. Design partner co-development. Playbooks built from what operators know works.
Learned from outcomes: execution feedback loop that teaches the model which intervention wins in which situation.
A competitor starting today has zero outcome data. Rivive's library grows with every account saved.
The library answers one question no incumbent can: Which playbook saves this type of account, at this stage, with these signals? Not a guess. A learned answer.
We don't wait for customers to find us. We route through ecosystems that already own the relationship.
Three channels. Each one compounds the next.
Investor portfolio distribution
One fund = 15–30 warm ICP intros. Every portfolio company has the same churn problem. Rivive becomes infrastructure recommended at onboarding.
Assessment-led direct
Paid Revenue Defense Assessment — €2900 entry point. Five business days. Gmail + Stripe + product analytics mapped and scored. Value delivered before platform decision. Walking away means going back blind.
RevOps & CS consultancies
Already inside ICP accounts. They surface the pain and recommend the fix. Revenue share creates near-zero CAC.
€900K to build the engine and prove the model.
The methodology is built. The round funds the product that scales it.
| Technical co-founder + first engineer | 45% | Own architecture, integration layer, and signal engine |
|---|---|---|
| Signal models & AI agents | 20% | Churn prediction layer and outcome-trained playbook engine |
| Design partner onboarding | 10% | First 5 platform conversions from assessment clients |
| GTM foundation | 15% | Assessment channel, partner outreach, first revenue |
| Runway buffer | 10% | 18-month runway to Series A metrics |
| Status | Timeline | Milestone |
|---|---|---|
| Now | Q2 2026 | Assessment outreach begins. First paying clients. Methodology proven in the market, not just in discovery. |
| Q2 2026 | Q2–Q3 2026 | Technical co-founder hired. v1 signal engine architecture complete. First integrations live: Gmail + Stripe + HubSpot. |
| Q3 2026 | Q3 2026 | v1 platform live with core churn agent. 3–5 design partners converted to platform subscriptions. |
| Q4 2026 | Q4 2026 | 8–10 paying customers. €250K–€350K ARR run rate. Proven signal-to-intervention loop with documented outcomes. |
| Series A | Q1 2027 | Series A ready. €600K+ ARR. Outcome-trained playbook engine with multi-customer outcome data. Gainsight displacement narrative live. |
Problem Validated
30+ hours of direct discovery with VP CS, CRO, and RevOps operators. Silent revenue leak confirmed independently across every conversation.
Methodology Built
Revenue Defense Assessment framework complete. Signal taxonomy defined. First assessments deploying April 2026.
Round Open
€900K seed. Pre-traction, post-validation. First institutional conversations underway.
The company that owns AI-native post-sale revenue defense for scaling SaaS will be worth billions. The window to build that moat is now.