IEP Companion – Agentic
Agentic IEP Management and Learning System

While traditional IEP teams review assessments sequentially, our agents simultaneously analyze WISC-V cognitive profiles, WJ-IV achievement data, BASC-3 behavioral patterns, speech-language evaluations, and OT assessments to identify hidden connections. For example, detecting that low processing speed (WISC-V SS 78) directly correlates with word problem difficulties (WJ-IV 1.6 GE) and attention issues (BASC-3 T-67), creating a unified intervention strategy impossible to see in isolation.

The system identifies subtle but critical performance patterns: Joel's calculation skills (1.9 GE) versus applied problem solving (1.6 GE) reveals the true barrier isn't mathematical reasoning but reading comprehension of word problems. This nuanced analysis leads to targeted vocabulary pre-teaching and visual supports rather than generic math intervention—a distinction that dramatically improves outcomes.

By analyzing social skills data (BASC-3 T-45, positive peer interactions during structured activities) alongside attention challenges, agents identify that Joel's social motivation can be leveraged for cooperative learning opportunities. This transforms a deficit-focused plan into a strength-based approach where peer collaboration becomes the vehicle for sustained attention and task completion.

Agents correlate Joel's 12-minute attention span with 67% task completion rate to prescribe precise break intervals (10-minute work segments with movement breaks) rather than generic "frequent breaks." This data-driven specificity ensures accommodations actually work rather than existing as vague suggestions teams struggle to implement.

The Goal Generation Agent doesn't just write SMART goals—it analyzes the gap between current performance (2.3 GE reading) and grade-level expectations, then creates developmental scaffolds. It recognizes that jumping directly to 4th-grade comprehension is unrealistic, instead targeting grade-level passages with 80% accuracy on literal and inferential questions—challenging yet achievable based on baseline data.

Agent 13's compliance validation goes beyond checking boxes—it analyzes whether Present Levels actually support the proposed goals, whether service minutes align with identified needs, whether LRE justification contains required elements, and whether assessment participation plans address all state testing requirements. This prevents the compliance gaps that lead to due process complaints.

By analyzing report card trends (Q1: 450KB, Q2: 460KB, Q3: 470KB), classroom work samples, and state test data across time, the system identifies growth trajectories and predicts which interventions will yield measurable progress. This transforms static snapshots into dynamic learning profiles that inform both current services and future planning.

The system synthesizes cognitive data (working memory SS 85, verbal comprehension SS 92) with behavioral observations (attention problems T-67) to reveal that Joel's behavioral challenges stem from cognitive overload, not willful noncompliance. This critical distinction shifts intervention from behavior management to cognitive supports like chunking information and providing processing time.

Rather than defaulting to standard service allocations, Agent 7 calculates precise service intensity based on the magnitude of need: 5 times weekly for 45 minutes in resource room reflects the 2+ year gap in reading and math, while 2 times weekly speech therapy addresses specific language comprehension deficits identified in evaluations. Every minute is justified by data.

Agents cross-reference medical reports, parent consent forms, prior written notices, procedural safeguards, and evaluation timelines to ensure internal consistency. If a medical report mentions ADHD but the IEP doesn't address attention supports, the system flags this gap. If parent concerns from initial meetings aren't reflected in goals, agents surface this discrepancy.

ABAS-3 data showing functional academics composite of 78 with age-appropriate daily living skills tells agents that Joel can generalize learning to real-world contexts. This insight drives recommendations for authentic application opportunities rather than isolated skill drill, making learning more meaningful and retention more likely.

What would take an IEP team 4-6 hours of meeting time (reviewing 28 documents, discussing assessments, debating goals, ensuring compliance) happens in under 40 seconds. But speed isn't the breakthrough—it's that all 15 agents work simultaneously, each bringing deep expertise to their domain, collaborating in ways impossible for sequential human processing.