Across states and counties, ETS consistently observes:

• Delayed access to school records, often weeks after placement changes
• Academic regression tied to mobility rather than ability
• High stigma around asking for help, especially among older youth
• Limited caregiver capacity, particularly outside school hours
• Inconsistent data visibility for caseworkers and agencies

Without new tools, even high-quality tutoring struggles to keep pace with the realities of foster care.

Quad-AI isn’t an add-on—it’s a natural extension of ETS’s origins in Pittsburgh (1996), where high-dosage tutoring was first used to keep foster youth in classrooms instead of crisis systems.

What that looks like in practice:

✓ Serves ages 5–18 facing placement instability, learning gaps, and trauma
✓ Builds individualized learning paths that adapt to disrupted schooling
✓ Targets equity gaps where traditional systems fall short (i.e. only ~70% of foster youth graduate high school vs. 86% nationally)

By embedding academic support within stability-focused design, Quad-AI delivers intervention at the moment it matters most.

The Student Portal offers gamified progress reports that track mastery across skills and subjects while flagging emotional or behavioral barriers early. This helps reduce stress, build confidence, and keep learning on track.

Key student-facing outcomes include:

✓ Clear visibility into skill mastery and growth
✓ Early identification of emotional or behavioral learning barriers

For families, the Parent Portal provides real-time oversight without adding burden. Parents can view:

✓ Scheduling and attendance
✓ Session summaries
✓ Progress alerts

Under the hood, Quad-AI operates through a hybrid human-AI model, combining expert tutors with adaptive AI prompts. Content is generated using multiple large language models—including Claude-3, GPT-4, Gemini Pro, and Perplexity—ensuring outputs are supportive, bias-checked, and responsive to each learner rather than purely algorithmic.