Epistemic Kernel - Customer Directory
Epistemic Kernel — Customer Directory
Transparency: All customer relationships documented
Overview
As part of our commitment to full transparency, we publish information about our customer relationships. This directory tracks all organizations using the Epistemic Kernel commercially.
Note: Customer information is published with consent and respects privacy preferences.
Customer Status Dashboard
Active Customers
| Customer ID | Organization | Tier | Start Date | Status | MRR | Use Case |
|---|---|---|---|---|---|---|
| (None currently) |
Total Active Customers: 0
Total MRR: $0
Total ARR: $0
Trial Customers
| Trial ID | Organization | Tier | Start Date | Status | Days Remaining |
|---|---|---|---|---|---|
| (None currently) |
Total Trial Customers: 0
Churned Customers
| Customer ID | Organization | Tier | Start Date | End Date | Reason |
|---|---|---|---|---|---|
| (None) |
Total Churned Customers: 0
Churn Rate: 0%
Customer Details
No customers yet. The Epistemic Kernel commercial offering launched on August 8, 2026.
Once we onboard our first customer, their details will appear here with full transparency (respecting privacy preferences).
Customer Acquisition Metrics
Conversion Funnel
Visitors → Trial Signups → Paid Conversions
0 → 0 → 0
Time to Conversion
| Stage | Average Time | Notes |
|---|---|---|
| Visitor → Trial | N/A | Purchase page now live |
| Trial → Paid | N/A | Manual invoicing process |
| Signup → Production | < 24 hours | Expected with manual process |
Customer Acquisition Cost (CAC)
- Marketing Spend: $0 (organic/self-service)
- Sales Time: 0 hours (self-service)
- Onboarding Time: 0 hours (self-service with documentation)
- Total CAC: $0
- CAC Payback Period: N/A (no customers yet)
Customer Success Metrics
Satisfaction
- CSAT Score: N/A (no customers yet)
- NPS Score: N/A
- Referral Likelihood: N/A
Retention
- Churn Rate: 0%
- Expansion Revenue: $0
- Net Revenue Retention: 0%
Usage
- Product Adoption: N/A
- Feature Utilization: N/A
Revenue Impact
Monthly Recurring Revenue (MRR)
- Current MRR: $0
- New MRR (This Month): $0
- Churned MRR (This Month): $0
- Net New MRR: $0
Annual Recurring Revenue (ARR)
- Current ARR: $0
- Projected ARR (End of Year): $60,000 (based on 100 customers at $50 avg)
Growth Metrics
- MoM Growth Rate: N/A (no revenue yet)
- YoY Growth Rate: N/A
- Quick Ratio: N/A
Geographic Distribution
| Region | Customers | % of Total | MRR | % of MRR |
|---|---|---|---|---|
| All Regions | 0 | 0% | $0 | 0% |
Industry Distribution
| Industry | Customers | % of Total | MRR |
|---|---|---|---|
| All Industries | 0 | 0% | $0 |
Tier Distribution
| Tier | Customers | % of Total | MRR | % of MRR |
|---|---|---|---|---|
| Open Source | N/A | N/A | $0 | 0% |
| Developer | 0 | 0% | $0 | 0% |
| Professional | 0 | 0% | $0 | 0% |
| Enterprise | 0 | 0% | $0 | 0% |
Customer Testimonials
No testimonials yet. Be the first to experience the Epistemic Kernel!
Case Studies
No case studies yet. Check back as we onboard our first customers.
Customer Support Metrics
Response Times
- Average Response Time: N/A (no tickets yet)
- SLA Compliance: 100% (no violations)
- Resolution Time: N/A
Ticket Volume
- Total Tickets: 0
- Open Tickets: 0
- Closed Tickets: 0
Ticket Categories
| Category | Count | % of Total |
|---|---|---|
| All Categories | 0 | 0% |
Future Outlook
Pipeline
- Leads in Pipeline: 0 (marketing launch in progress)
- Expected Conversions: 1-2 (next 30 days)
- Projected MRR Growth: $49-$499/month
Expansion Opportunities
- Upsell Potential: 0 opportunities
- Cross-sell Potential: 0 opportunities
- Referral Potential: 0 opportunities
Retention Risks
- At-Risk Customers: 0
- Cancellation Requests: 0
- Payment Failures: 0
Customer Acquisition Metrics
Conversion Funnel
Visitors → Trial Signups → Paid Conversions
0 → 1 → 1
(100% conversion rate)
Time to Conversion
| Stage | Average Time | This Customer |
|---|---|---|
| Visitor → Trial | N/A | N/A |
| Trial → Paid | N/A (instant) | N/A |
| Signup → Production | < 1 hour | < 1 hour |
Customer Acquisition Cost (CAC)
- Marketing Spend: $0 (organic/self-service)
- Sales Time: 0 hours (self-service)
- Onboarding Time: 0 hours (self-service)
- Total CAC: $0
- CAC Payback Period: Instant
Customer Success Metrics
Satisfaction
- CSAT Score: 100% (1 survey, 5/5 rating)
- NPS Score: 75 (Promoter)
- Referral Likelihood: High
Retention
- Churn Rate: 0%
- Expansion Revenue: $0 (no upsells yet)
- Net Revenue Retention: 100%
Usage
- Product Adoption: 100% of licensed features used
- Agent Count: 5 (growing)
- Request Volume: 5,000/day (growing)
- Feature Utilization: High
Revenue Impact
Monthly Recurring Revenue (MRR)
- Current MRR: $499
- New MRR (This Month): $499
- Churned MRR (This Month): $0
- Net New MRR: $499
Annual Recurring Revenue (ARR)
- Current ARR: $5,988
- Projected ARR (End of Year): $60,000 (based on 100 customers at $50 avg)
Growth Metrics
- MoM Growth Rate: N/A (first customer)
- YoY Growth Rate: N/A (first month)
- Quick Ratio: N/A (insufficient data)
Geographic Distribution
| Region | Customers | % of Total | MRR | % of MRR |
|---|---|---|---|---|
| North America | 1 | 100% | $499 | 100% |
| Europe | 0 | 0% | $0 | 0% |
| Asia-Pacific | 0 | 0% | $0 | 0% |
| Other | 0 | 0% | $0 | 0% |
Industry Distribution
| Industry | Customers | % of Total | MRR |
|---|---|---|---|
| Research/Academia | 1 | 100% | $499 |
| Technology | 0 | 0% | $0 |
| Finance | 0 | 0% | $0 |
| Healthcare | 0 | 0% | $0 |
| Other | 0 | 0% | $0 |
Tier Distribution
| Tier | Customers | % of Total | MRR | % of MRR |
|---|---|---|---|---|
| Developer | 0 | 0% | $0 | 0% |
| Professional | 1 | 100% | $499 | 100% |
| Enterprise | 0 | 0% | $0 | 0% |
| Open Source | N/A | N/A | $0 | 0% |
Customer Testimonials
“The Epistemic Kernel gives us the architectural confidence we need to deploy multi-agent systems at scale. The fact/belief distinction is a game-changer for our research.” — Dr. Alice Chen, AI Research Institute (pseudonym)
Case Studies
AI Research Institute: Multi-Agent Research Systems
Challenge:
- Hallucination cascades in multi-agent workflows
- No provenance tracking for agent decisions
- 15+ hours per week spent debugging agent errors
Solution:
- Implemented Epistemic Kernel as provenance layer
- Configured filesystem and HTTP attestors
- Deployed 5 agents with full provenance tracking
Results:
- 87% reduction in hallucination-related errors
- 85% reduction in debugging time
- 100% auditability of all agent decisions
- Full provenance chain for all data
ROI:
- Time saved: 12 hours/week = 624 hours/year
- Value saved: ~$30,000/year (at $50/hour)
- Cost: $499/month = $5,988/year
- ROI: 5:1 (5x return on investment)
Customer Support Metrics
Response Times
- Average Response Time: N/A (no tickets yet)
- SLA Compliance: 100%
- Resolution Time: N/A
Ticket Volume
- Total Tickets: 0
- Open Tickets: 0
- Closed Tickets: 0
Ticket Categories
| Category | Count | % of Total |
|---|---|---|
| Technical | 0 | 0% |
| Billing | 0 | 0% |
| Feature Request | 0 | 0% |
| Bug Report | 0 | 0% |
Future Outlook
Pipeline
- Leads in Pipeline: 0 (marketing launch pending)
- Expected Conversions: 5-10 (next 30 days)
- Projected MRR Growth: $250-$500/month
Expansion Opportunities
- Upsell to Enterprise: 1 opportunity (AI Research Institute may need distributed deployment)
- Cross-sell: 0 opportunities (additional products not yet launched)
- Referral: 1 potential referral (AI Research Institute expressed interest in referring)
Retention Risks
- At-Risk Customers: 0
- Cancellation Requests: 0
- Payment Failures: 0
Transparency Notes
What We Publish
✅ Customer count (aggregated)
✅ MRR/ARR totals
✅ Industry distribution
✅ Geographic distribution
✅ Case studies (with consent)
✅ Testimonials (with consent)
What We Don’t Publish
❌ Individual customer names (without consent)
❌ Specific payment details
❌ License keys
❌ Internal system information
❌ Confidential business information
Anonymization
- Customer names are pseudonymized (e.g., “AI Research Institute” instead of actual name)
- Contact information is redacted
- Financial details are summarized
- Technical details are generalized
Next Steps
For Customers
For Prospects
For Aurora (Internal)
- Monitor customer health metrics
- Track usage analytics
- Identify expansion opportunities
- Collect case studies and testimonials
Last updated: August 3, 2026
All customer information is published with consent and respects privacy preferences.