$1 vs $5
Slide 01
The opportunity
Growth at all costs is dead.
NRR is the new battlefield.
The AI-native infrastructure to win it doesn't exist yet.
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.
6–8 weeks
Before churn surfaces in a dashboard
NRR
The metric every SaaS investor asks about first
Every part of SaaS revenue has infrastructure protecting it — except the revenue you've already closed. Rivive is building that infrastructure.
Slide 02
Founder story
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.
1
Failed founder
Built and lost a startup. Accounts left unseen. The system to act didn't exist.
2
Witnessed market blindness
Worked in business development at a music startup and saw a founder-driven company stay blind to customer signals.
3
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.
4
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.
Slide 03
The gap nobody owns
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.
Slide 04
The contrarian bet
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.
The cardiologist analogy
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.
Slide 05
Signal quality
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.
Response latency trends, thread participation decay, initiation ratio shifts, and champion engagement fade.
Seat utilization trends, payment timing changes, and expansion versus contraction signals.
Login frequency decay, feature adoption depth, and session length over 6 weeks.
Internal signal only
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.
Slide 06
Market entry & ambition
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.
$1M–15M ARR
→
$15M–50M ARR
Expansion motion
→
Gainsight's market
Slide 07
Why we win
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 |
To copy Rivive, Gainsight would have to reject their own premise. That's a company rebuild, not a feature sprint.
Slide 08
The self-improving engine
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.
1
Seed phase
Engineered from discovery: 30+ interviews with VP CS, CRO, and RevOps. Design partner co-development. Playbooks built from what operators know works.
2
Scale phase
Learned from outcomes: execution feedback loop that teaches the model which intervention wins in which situation.
3
The compounding moat
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.
Slide 09
Distribution edge
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
Free Revenue Risk Assessment. Gmail + Stripe + product analytics in minutes. Value before purchase decision. Walking away means going blind again.
RevOps & CS consultancies
Already inside ICP accounts. They surface the pain and recommend the fix. Revenue share creates near-zero CAC.
Free assessment
Signal report
Design partnership
Platform subscription
Slide 10
The ask
€300K to build the team and prove the model.
The market timing is now. NRR is the new growth metric. Post-sale infrastructure is the gap every SaaS investor is watching. The window to own this category is open — and closing.
| Product & core platform | 40% |
|---|---|
| Signal models & agents | 20% |
| Design partner onboarding | 15% |
| GTM foundation | 15% |
| Runway | 10% |
| Q3 2026 | v1 platform live with core churn agent |
|---|---|
| Q3 2026 | 6–10 paid assessments completed |
| Q4 2026 | 4–6 pilot conversions to platform |
| Q4 2026 | 5+ subscription logos and recurring revenue |
| Q1 2027 | €600K ARR run rate and series A ready |
The company that owns AI-native post-sale revenue defense for scaling SaaS will be worth billions. The infrastructure doesn't exist yet. Rivive is building it — and the window to lead this category is open right now.
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