Most SaaS companies don't lose customers. They watch them 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 infrastructure.
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 customer success operator inside a 100+ person CS organization. Managing €2M+ accounts with daily hands-on exposure to Gainsight — not in a demo, in practice. Watched the signal-to-action gap cost real revenue in real time, repeatedly, with no systemic fix available.
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 am building Rivive while employed — deliberately. I have financial obligations I take seriously and I'm not going to burn my income before I have capital to replace it. That's not a lack of conviction. It's the same risk discipline I'll apply to your capital. I go 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 — three times, from three different angles.
Failed founder
Built and lost a startup. Accounts left unseen. The system to act didn't exist.
Witnessed market blindness
Worked in business development at a music startup and saw a founder-driven company stay blind to customer signals.
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.
I'm not building Rivive because I spotted a gap. I'm building it because I've lived every side of this failure — and I know exactly what the fix looks like.
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. Nobody owns that layer.
The CS industry has a data hoarding problem. We're betting against it.
Companies bought Gainsight and spent 3 years filling it with data that still can't tell a CSM what to do on Monday morning.
More data = better retention
CSMs feed systems instead of saving accounts. Manual health scores become bias masquerading as intelligence.
Right signals + right action = better retention
10% of the right behavioral data 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 and how to act. Rivive does the same for customer health: continuous behavioral monitoring across email, billing, and product usage, so your CS team intervenes with precision instead of panic — and before it's 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 participation decay, initiation ratio shifts, 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
Slack — internal use only. CSM sentiment in team channels and convergence signals when sales, support, and CS discuss the same account.
Connect Gmail, Stripe, and your product analytics. Give us 6 weeks of history. We'll show you which accounts are drifting — without asking your team to log 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 trojan horse logic
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 the next version of the playbook. This is the moat that 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 to flying 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 prepare the model for the next round and global upscale.
The methodology is built. The market is ready. This round funds the product that delivers it at scale.
| Technical co-founder + first engineer | 45% | Own architecture, integration layer, and signal engine |
|---|---|---|
| Signal models & AI agents | 20% | Churn prediction layer and self-improving 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. Self-improving 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 across B2B SaaS. Silent revenue leak confirmed independently across every conversation.
Methodology Built
Revenue Defense Assessment framework complete. Signal taxonomy defined. Audit tool in final build. First assessments deploying April 2026.
Round Open
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.