LEAPGENIX · MOBILE APPS + ON-DEVICE AI

Private AI apps for learning, growth and fitness.

LeapGenix is building three families of mobile apps — kids' education, personal development and AI fitness coaching — powered by our research into language models that run on the phone itself. All three are launching soon.

MEET THE APPS ↓

WHAT WE'RE BUILDING

Three app families.
One on-device intelligence.

Each app takes on a different everyday challenge. Underneath, they share one idea: AI should be helpful, personal and private, so wherever possible it runs on your phone instead of someone else's server.

★Little ChampionComing soon

KIDS EDUCATION

Where curiosity becomes confidence.

A playful learning app for children that turns lessons into short adventures, adapts to each child's pace, and celebrates every step, with an on-device AI companion designed for young learners.

  • ✦Learning through play
  • ✦Paced for every child
  • ✦Kid-safe on-device AI
Discover Little Champion ↗
↗ForgeLiftComing soon

PERSONAL DEVELOPMENT

Turn your vision into today's plan.

A personal development app that connects your life vision to measurable goals, quarterly targets, weekly commitments and daily time blocks, with private AI guidance that helps you plan and reflect.

  • ✦Vision to daily plan
  • ✦Weekly execution system
  • ✦Private AI planning help
Discover ForgeLift ↗
✦AIFitCoachComing soon

AI FITNESS COACHING

Your fitness journey, intelligently guided.

An AI fitness coach app that builds workouts around your goals, energy and schedule, answers training questions, and keeps you accountable, with coaching designed to run right on your phone.

  • ✦Adaptive workout plans
  • ✦Ask-anything AI coach
  • ✦Designed to work offline
Discover AIFitCoach ↗

ON-DEVICE LLM RESEARCH

Language models that run
in your pocket.

Alongside the apps, we research how to make small language models genuinely useful on everyday phones, so they can work privately, offline and without waiting on a server.

01
✦

Compact models

Choosing and adapting small language models that fit in a phone's memory without losing the skills each app needs.

02
✦

Quantization

Compressing model weights so they load faster, take less storage and run on mid-range devices.

03
✦

Mobile inference

Running models on phone CPUs, GPUs and neural accelerators while respecting battery life and heat.

04
✦

Private personalization

Adapting to each person's progress and preferences with context that stays on the device.

05
✦

Safety for every audience

Age-appropriate guardrails for children and careful boundaries for fitness guidance.

06
✦

Real-device evaluation

Testing quality, speed and battery impact on the kinds of phones people actually own.

Read about our research →

WHY ON-DEVICE

AI that stays close to
the people it helps.

01

Private by design

Children's learning, personal goals and fitness data are sensitive. Keeping AI on the device keeps that data close to the person it belongs to.

↗
02

Works offline

Help shouldn't disappear in a gym basement, on a bus or when the connection drops. Local models keep working without a signal.

↗
03

Instant responses

No round-trip to a server means answers that feel immediate, even on slower networks.

↗
04

Within reach

Built for everyday phones, with fewer cloud costs, so helpful tools can reach more families.

↗