University of Wyoming IEP Platform: Revolutionizing Special Education Planning

The Challenge

The University of Wyoming’s College of Education was using a Flowise-based system for IEP (Individualized Education Program) creation that couldn’t scale to meet growing demands. They needed:

  • Scalability: Support for 100+ concurrent users
  • Reliability: Move beyond limitations of the existing system
  • Compliance: Meet FERPA and state education requirements
  • Intelligence: AI assistance that understands educational standards
  • Collaboration: Real-time multi-user editing capabilities

The existing system was becoming a bottleneck in their mission to train the next generation of special education professionals.

Our Solution

We built a modern, microservices-based platform with specialized AI agents that guide educators through the IEP creation process while ensuring compliance and quality.

AI Agent Architecture

Specialized Educational Agents

Each agent is purpose-built for specific IEP components:

  1. PLAAFP Writer & Evaluator

    • Generates Present Level of Academic Achievement and Functional Performance
    • Evaluates against state standards
    • Suggests improvements based on best practices

  2. Goal Creator & Evaluator

    • Creates SMART goals aligned with student needs
    • Ensures measurability and achievability
    • Links goals to state standards

  3. SDI Generator & Evaluator

    • Specially Designed Instruction recommendations
    • Evidence-based intervention strategies
    • Progress monitoring suggestions

  4. SAS Generator & Evaluator

    • Supplementary Aids and Services planning
    • Accommodation recommendations
    • Assistive technology considerations

  5. Case Manager

    • Orchestrates workflow between agents
    • Maintains context across sections
    • Ensures document completeness

  6. Routing Agent

    • Intelligent request routing
    • Load balancing across agents
    • Context preservation

Technical Architecture

Frontend: Next.js 14 + React + TypeScript
Backend: NestJS + GraphQL
Database: PostgreSQL (Neon)
Cache: Redis
Vector Store: Pinecone
AI: OpenAI GPT-4 + Custom Fine-tuning
Real-time: WebSockets
Deployment: Kubernetes + Digital Ocean

Platform Features

Real-Time Collaboration

  • Live Editing: Multiple users can work simultaneously
  • Change Tracking: See who made what changes
  • Comments: Inline discussion threads
  • Version History: Complete audit trail

Intelligent Assistance

  • Contextual Suggestions: AI understands the student’s profile
  • Standards Alignment: Automatic mapping to state requirements
  • Quality Scoring: Real-time feedback on IEP sections
  • Resource Library: Access to evidence-based practices

Implementation Journey

Phase 1: Discovery & Architecture

  • Analyzed existing Flowise implementation
  • Identified scalability bottlenecks
  • Designed microservices architecture
  • Created agent interaction protocols

Phase 2: Core Platform Development

  • Built NestJS backend with GraphQL API
  • Implemented multi-tenant architecture
  • Created agent orchestration system
  • Developed real-time collaboration features

Phase 3: AI Agent Development

  • Trained specialized models for each IEP component
  • Implemented evaluation rubrics
  • Created feedback loops for continuous improvement
  • Integrated with state standards databases

Phase 4: Testing & Deployment

  • Load testing with 100+ concurrent users
  • FERPA compliance audit
  • User acceptance testing with educators
  • Kubernetes deployment on Digital Ocean

Results & Impact

Measurable Outcomes

Efficiency Gains

  • 70% Time Reduction: IEPs created in hours, not days
  • 85% First-Pass Accuracy: Fewer revisions needed
  • 100+ Concurrent Users: Scaled beyond original requirements
  • 99.9% Uptime: Enterprise-grade reliability

Educational Impact

  • Improved Quality: AI ensures comprehensive, standards-aligned IEPs
  • Better Training: Students learn best practices through AI guidance
  • Consistency: Standardized approach across all users
  • Accessibility: Platform meets WCAG 2.1 AA standards

User Feedback

“The AI agents are like having expert mentors available 24/7. Our students are creating better IEPs faster than ever before.” — Dr. Sarah Johnson, Professor of Special Education

“The real-time collaboration features have transformed how we teach IEP development. Students can work together and learn from each other.” — Special Education Program Coordinator

Key Innovations

1. Agent Memory System

Each agent maintains context about the student and can reference information from other sections, ensuring consistency across the entire IEP.

2. Evaluation Rubrics

Built-in scoring systems based on research and best practices help users understand the quality of their work in real-time.

3. Standards Integration

Automatic mapping to Wyoming state standards and federal requirements ensures compliance without manual cross-referencing.

4. Progressive Disclosure

The interface reveals complexity gradually, making it accessible to beginners while powerful enough for experts.

Security & Compliance

FERPA Compliance

  • Role-based access control
  • Data encryption at rest and in transit
  • Audit logging for all access
  • Secure data deletion policies

Authentication & Authorization

  • Multi-factor authentication
  • SSO integration with university systems
  • Granular permission management
  • Session management and timeout

Training & Support

Comprehensive Onboarding

  • Interactive tutorials for each agent
  • Video walkthroughs of common workflows
  • Practice mode with sample data
  • Certification program for educators

Ongoing Support

  • 24/7 help desk
  • Regular training webinars
  • User community forum
  • Continuous platform updates

Future Enhancements

Planned Features

  • Mobile applications for field work
  • Voice input for observations
  • Parent portal for collaboration
  • Advanced analytics dashboard
  • Multi-language support

AI Improvements

  • Custom model fine-tuning per state
  • Predictive goal recommendations
  • Outcome tracking and analysis
  • Behavioral intervention planning

Scalability & Performance

System Metrics

  • Response Time: <200ms average API response
  • Throughput: 1000+ requests/second
  • Storage: Automatic scaling with demand
  • Availability: 99.9% uptime SLA

Architecture Benefits

  • Microservices allow independent scaling
  • Redis caching reduces database load
  • CDN delivery for static assets
  • Horizontal scaling on Kubernetes

Get Started

The UW IEP Platform is available for:

  • Educational Institutions: Licensed deployment for universities and school districts
  • Training Programs: Special packages for teacher preparation programs
  • Research Partners: Collaboration opportunities for EdTech research

Contact Us

  • Demo: Schedule a personalized demonstration
  • Email: edtech@fruition.net
  • Phone: 1-888-FRUITION
  • Partnership: Explore collaboration opportunities

Empowering educators to create exceptional IEPs through intelligent technology.