COG Learning Tools

COG Learning Tools
One-Liner

COG Learning Tools developed REED (Read, Engage, Explore, Discuss), a mobile application that transforms family reading time.

Built on decades of developmental research, REED’s patent-pending question-generation engine creates customized conversation starters for any children’s book, helping caregivers and educators spark richer dialogue and build early literacy skills.

The technology bridges the gap between research and everyday reading, turning storytime into a scalable intervention to ensure school readiness and combat the literacy crisis.

Institution
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Company Info

Nearly one-third of U.S. children enter kindergarten without foundational skills needed to thrive (NCES, 2022). These early gaps widen over time—by third grade, reading proficiency predicts high-school graduation with 90% accuracy, and children who struggle by age nine are four times more likely to leave school without a diploma.

Limited early language exposure is linked to lower lifetime earnings, health, and well-being. COG Learning’s mission is to make evidence-based early learning accessible to every child through practical, scalable tools for families and educators.

REED is a reading companion that helps adults turn storytime into rich dialogue proven to boost vocabulary, comprehension, and a love of reading. Using developmental science and generative AI, REED suggests developmentally appropriate conversation prompts for any children’s book—making it scalable, adaptable, and inclusive across diverse contexts. It works offline for home and classroom use.

In pilot testing with 71 families:

  • Children responded to 91% of questions parents asked
  • Averaged four conversational turns per prompt
  • 85% of parents rated REED easy to use
  • 100% wanted notification when the app launches

Unlike screen-time apps that replace interaction, REED amplifies human connection—empowering adults to supercharge children’s learning.

Team Members

Leadership Team

  • Dr. Amy Booth – Board Chair
    Directs the Little Learners Lab at Vanderbilt with 20+ years of expertise in child development. Ensures REED remains grounded in developmental science and ethical research.
  • Dr. Abigail Petulante – CTO
    Data scientist with Vanderbilt Data Science Institute. Leads AI development and system design; recently collaborated with IBM on proof-of-concept validation of REED’s model training.
  • Dr. Margaret Shavlik – CEO
    Leads commercialization, partnerships, and user research. Manages pilots, publisher collaborations, and strategy with support from Vanderbilt CTTC, The Wond’ry, LaunchTN, and external mentors.

The core team has collaborated for over two years (Shavlik and Booth for over nine), completed NSF I-Corps in 2024, and secured multiple research grants. Their expertise in developmental psychology, AI engineering, and research translation—backed by strong institutional support—positions COG Learning to scale REED’s impact.

Go-To-Market Strategy

The global early-childhood EdTech market exceeds $13 billion with 16% CAGR, preschool ages representing over 53% of revenue.

COG Learning’s strategy starts with B2B2C partnerships through trusted hubs—libraries, literacy nonprofits, and early-childhood centers—to reach families at scale, build credibility, and generate pilot data.

Key Focus Areas

  • Institutional Partners
    Enhance family programming with measurable engagement and impact data.
  • Decision-Makers
    Library systems, early-learning administrators, curriculum/digital-resource directors.
  • Pilot Structure
    6–12 month implementations with tracking, surveys, and reporting leading to tiered annual licensing.

Active Discussions & Interest

  • Nashville Public Library, Reading Is Fundamental, GELF – program pilots and statewide expansion
  • Flowerpot Press, Cherry Lake Publishing, Gibbs Smith, BookSpring – content integration
  • Scholastic, OverDrive, Epic! Books – expressed interest in future collaborations

Following institutional rollout, expansion will include tiered family plans (B2C) and enterprise licensing (B2B) for publishers integrating REED’s engine.

Revenue Generation

COG Learning (incorporated October 2025) is pre-revenue with a diversified model targeting institutional, consumer, and enterprise channels.

Serviceable market includes 7,000+ public library systems and nearly 2,000 literacy nonprofits reaching over 40 million U.S. families.

Three Complementary Revenue Streams

Stream Channel Description
Content Access B2B2C & B2C Institutional sponsors provide family access via annual licenses (tiered for multilingual content, training, reporting).
Consumer: Free with open-source books; paid subscriptions for premium features.
Technology Licensing B2B Publishers and platforms license REED’s question-generation engine via API or white-label integration for eBook ecosystems.
Data & Analytics Services B2B Aggregated insights on reading behavior and content performance, tapping into $13B learning-analytics and $1.4B reading-analytics markets.

Future opportunities include affiliate revenue and sponsored content.

Benefits From Showcase

Investment Opportunity

COG Learning is raising a $1.1M Seed Round for 24 months of runway to transition REED from pilot to full market launch and achieve product-market fit.

Use of Proceeds

Area Percentage Focus
Technology & Product Development 74% Software engineering, app development, cloud hosting, book licensing, infrastructure
Growth & Partnerships 17% Marketing, customer discovery, pilot expansion, strategic outreach
Operations & Legal 9% Compliance, insurance, administrative stability

Key Milestones

  • Launch REED 1.0 with verified usability and engagement metrics from multi-site pilots
  • Convert institutional partners into paying customers via early-adopter agreements
  • Secure at least one major technology-licensing agreement with demonstrated ROI

Existing traction includes over $390,000 in research/pre-seed funding, investor interest, matching opportunities (InvestTN, Vanderbilt), and planned NIH SBIR/STTR submission in 2026.

Technology Assesment

COG Learning has developed a functional, research-validated prototype of REED for iOS and Android.

While caregivers read a storybook, REED listens, follows the narration via speech-to-text, matches stored text, and displays developmentally appropriate question suggestions. Caregivers choose which to ask, keeping interaction human-centered.

The proprietary model uses a patent-pending fine-tuning approach with licensed/open-source books, expert-curated questions, and reinforcement feedback. Questions are pre-generated and packaged for offline use.

An expanded pilot is underway (families using REED for two weeks) to refine usability, adaptability, and engagement. Transition to commercial-grade product includes scalable architecture, analytics dashboards, and API integrations.

Strong IP position: Vanderbilt licensing option and provisional patent.

Money Received

To date, COG Learning has secured over $200,000 in non-dilutive research funding and $192,000 in pre-seed capital, plus significant in-kind support.

Funding Sources

 

Source Amount Purpose/Notes
Vanderbilt CTTC Innovation Catalyst Fund $9,780 (2024–25) + $18,500 (2025–26) Software development, infrastructure, pilot compensation
Vanderbilt Generative AI SEED Grant $17,280 (2024–25) Prototype development, model training
Vanderbilt LIVE Learning Incubator SPARK Grant $10,000 + in-kind (2024–25) App prototyping, pilot testing
Private Donation Research Fund $50,000 (unrestricted) Bridge funding for research staff
NSF I-Corps Team Grant $50,000 (2024–25) Customer discovery, early R&D
Dollar General Family Literacy Grant $9,500 (2025–26) Book and software costs for users
Vanderbilt Data Science Institute (Data Science for Social Good) $30,000 (2023) + $21,000 (2025) Prototype development, model training stipends
Dean of Peabody College Pilot Research Grant (Pre-seed) $192,244 + in-kind (2024–25) Salary support, commercialization; 10% founder equity

In-kind support includes computing resources and server infrastructure from Vanderbilt partners.

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