™Learn AI.
Build for the
next generation.
A standalone AI learning environment that stays at school. Trained high-school students build applications for K–5. Middle-school students develop the skills to become the next builders.
9–12 build teacher-reviewed apps for K–5
Stage the models, curriculum, software, and dependencies locally. Run learning, development, and approved applications over a local school network without an internet connection.
Today's learners.
Tomorrow's builders.
Each grade band has a different role.
Explore how they contribute to the same environment.
Turn AI skills into apps for younger learners.
The vision starts with high-school students who have already been trained in AI and application building. They use Hawkeye IDE, on-box LLMs, and approved curriculum datasets to create offline applications for K–5 classrooms.
- Translate an elementary teacher's lesson brief into an application.
- Build, inspect, and test the code using local AI assistance.
- Submit the app for educator review, then improve it using classroom feedback.
Approved applications return to K–5 classrooms.
Built by students.
Reviewed by educators.
Illustrative projects show how each grade band
can take part in the same learning cycle.
Word Explorer
Create a guided word-and-picture activity from a teacher's vocabulary list.
Practice the underlying AI skillsCompare two prompts and check whether every example uses the approved vocabulary.
Build the applicationBuild a simple word activity with teacher-selected content and a clear retry path.
Educator reviewThe teacher checks vocabulary, reading level, and every activity before classroom use.
Use it in the classroomStudents use the approved app in a teacher-led lesson. Feedback goes back to the builders.
Everything they need.
Inside your boundary.
Choose a local footprint for your learning environment.
Size the hardware for the models and concurrent users.
A school-controlled application and learning host.
Use the Hawkeye Hypervisor on bare metal to host the platform and separate learning applications in isolated virtual machines. Student devices connect through the school's local network.
ETL / ELT · searchLocal intelligenceOn-box LLMs · GPUs
AI agents · analytics
No external inference or runtime downloads
Your idea. Your local AI. Your application.
Vibe code with an on-box LLM, your approved datasets, and Hawkeye features. Plan, build, and test a separate application, then deploy it offline on your private foundation.
Build the skills.
Keep the opportunity local.
A school-owned environment for learning AI, creating applications,
and sharing student-built tools across grade levels.