SafeMinds AI: Responsible AI for Growing Minds
Pre-seed AI-native child learning and safety platform
MVP in development | Beta launching Q4 2026
We're building the supervision layer between children and generative AI—combining smart, age-appropriate chat with real-time parent oversight and anti-cheating safeguards.
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The Problem
Up to 86% of students are already using AI tools for learning, and more than 75% use AI for homework assistance.
Parents and educators are worried about AI's impact on:
  • Child safety
  • Integrity
  • Critical thinking
The AI in education market is growing at ~30% annually, signaling rapid and irreversible adoption in schools and homes.
The Solution
We are building the supervision layer between children and generative AI.
Smart, safe, and age-appropriate chat
SafeMinds AI is a kid-first chat app with built-in moderation and parent alerts, so children can explore AI responsibly.
Real-time alerts and locked history for parents
Real-time alerts and locked history give parents complete visibility and oversight.
No shortcuts or cheating—just guided learning
A safe, structured AI experience that helps kids think critically, stay within ethical boundaries, and learn without shortcuts or cheating.
Designed to build critical thinking, not bypass it
Defensibility Architecture
Age-Tiered AI Routing System
Routes every interaction through grade-specific logic layers to enforce age-appropriate language, complexity, and topic boundaries.
Parent Oversight Engine
Provides structured visibility, alerts, and configurable controls across all child interactions.
Anti-Cheating Enforcement Layer
Prevents intentional cheating by guiding students through structured reasoning and learning prompts.
Structured Response Constraints
Applies predefined response constraints to limit unsafe, manipulative, or developmentally inappropriate outputs.
Data-Driven Safety Refinement
Continuously improves guardrails and interaction logic based on real-world supervised usage patterns.
Market Opportunity
Total Addressable Market (TAM)
There are roughly 50 million school-age children in the U.S., representing the broadest potential audience for AI-augmented learning and supervision.
Serviceable Available Market (SAM)
Within that group, an estimated 10–15 million families are already actively using AI tools for schoolwork and study, reflecting current adoption among students and educators.
Serviceable Obtainable Market (SOM)
Our initial target focus in Years 1–2 is tech-aware families with children ages 6–14, a wedge segment where early traction and retention are most likely to form.
AI in Education Is a Fast-Growing Market
The global AI in education market is projected to grow at approximately 30-40 % annual CAGR through 2030, expanding from a multi-billion-dollar industry today to several times its size by the end of the decade.
Competitive Advantage
Built for COPPA Compliance from Day One
Designed specifically for minors, with privacy, data handling, and regulatory alignment embedded into the architecture, not retrofitted.
Purpose-Built Supervision Architecture
A structured safety and oversight system layered on top of AI, engineered for monitored child use rather than open-ended interaction.
Parent + Child Dual-Interface Design
Separate but connected experiences: kids interact with AI; parents retain visibility, alerts, and control.
Data Feedback Loop Improves Safety Over Time
Supervised real-world usage continuously refines response constraints, guardrails, and behavioral logic.
Strategic Positioning
Large AI providers optimize for scale and engagement; we optimize for supervised minors and learning enhancement.
Go-To-Market Strategy
Phase 1: Controlled Beta (0–6 Months)
  • 20–50 tech-aware families (ages 6–14 focus)
  • Full instrumentation: usage, feature adoption, retention tracking
  • Validate monthly retention and parent engagement behavior
Goal: Prove sustained usage and safety trust before scaling
Phase 2: Paid CAC Testing (6–12 Months)
  • Small-budget ad experiments across 2–3 channels
  • Landing page + onboarding funnel optimization
  • Conversion rate + cost-per-acquisition validation
Goal: Establish repeatable acquisition channel with viable LTV:CAC dynamics
Phase 3: Scalable Acquisition (Post-Validation)
  • Direct-to-consumer subscription growth
  • Referral loops + parent community expansion
  • Selective school pilot programs (only if retention validated)
Goal: Expand from validated segment to broader adoption
Business Model - Early Stage
Individual Plans - Entry Level
$4.99/mo or $39.99/year per child
Family Bundles - Entry Level
$7.99/mo or $69.99/year for multiple children
School Licenses
$2-$5 per student annually depending on tier
Add-On Revenue
Curriculum packs and premium reporting features
$7
Blended ARPU
per month
6-8%
Monthly Churn
average
12-16
Average Lifetime
months
70-80%
Gross Margin
projected
$35-50
Early CAC
estimated
$60-80
Gross LTV
estimated
3:1
Target LTV:CAC
ratio
CAC to be validated through controlled paid testing. Target 3:1 LTV:CAC before scaling marketing.
Use of Funds ($500,000)
1
Product Development & Engineering - $250,000
  • Dedicated contract engineering (frontend + backend)
  • MVP completion → stable beta → iteration cycle
  • Supervision architecture build-out (age-tier routing, safety logic, anti-cheating enforcement)
  • Parent dashboard + reporting system stabilization
  • Instrumentation & analytics for retention tracking
2
AI Infrastructure & Cloud Operations - $50,000
  • LLM API usage (OpenAI)
  • Secure AWS hosting + scalable backend architecture
  • Encrypted storage & logging
  • Monitoring, error tracking, and compute optimization
3
Compliance, Legal & Risk Mitigation – $50,000
  • Delaware C-Corp conversion
  • Standard SAFE documentation
  • COPPA-compliant policy & consent framework
  • Data protection audit
  • Trademark filing & IP review
4
Go-To-Market & Customer Acquisition – $75,000
  • Controlled paid CAC testing (Meta + parent channels)
  • Conversion funnel optimization
  • Landing page & onboarding refinement
  • Community building and referral programs
5
User Research & Pilot Expansion – $30,000
  • Beta tester incentives
  • Structured parent and educator interviews
  • Early pilot programs (schools / homeschool groups)
  • Usage & retention behavior analysis
6
Working Capital & Runway Buffer – $45,000
  • Variable AI usage overages
  • Legal/compliance adjustments
  • Infrastructure scaling surprises
Designed to provide 18-24 months of disciplined runway through MVP completion and validation milestones.
Investment Opportunity
Raising: $500,000 via SAFE
Target runway: 18–24 months
Key milestones:
MVP completion
100 beta families
Retention validation
Early revenue conversion
Delaware C-Corp conversion + compliance structure
Building Responsible AI for Growing Minds
Meet the Team
Jaclyn Kilani
Co-Founder | Engineering & Product
  • Web developer leading core architecture and AI integration
  • Background in marketing and design
  • Driving MVP completion and technical execution
Catherine Isbell
Co-Founder | Product Strategy & Operations
  • 17 years in operational and product management leadership
  • Experienced in launching and scaling complex tech products
  • Leading roadmap, compliance planning, and go-to-market execution
Why Us
Technical founders with hands-on execution capability
Mothers of school-age children directly experiencing the AI shift
Building the supervised AI platform we want our own families to use
Mom tech founders, parenting the AI generation
Interested in Learning More?
We’re raising $500,000 to build the leading responsible AI platform for families.
If you believe the future of AI must include safety, oversight, and critical thinking for children, we’d welcome a conversation.

Contact Us
Jaclyn Kilani
Co-Founder | Engineering & Product
Catherine Isbell
Co-Founder | Product Strategy & Operations
Or use the form below to send us a message directly.