Responsible AI
57% of special education teachers are using ChatGPT, Gemini, or similar public AI to draft IEP goals — up from 39% the year before. They're uploading student names, disabilities, and test scores to public services because their actual tools don't help them. Accord gives them AI that's trustworthy.
Teachers spend 30–60 hours per year per student on IEP documentation. With caseloads of 20+ students, that's months of their lives going to paperwork instead of instruction. When the software doesn't help, they reach for whatever does — regardless of compliance risk.
The result: student PII uploaded to public AI services. Generic goals that don't fit the student. FERPA violations your district is liable for. And teachers who are still burning out, just slightly faster.
The answer isn't banning AI. It's providing AI that's safe, useful, and under the teacher's control.
AI in Accord follows a simple loop: the teacher provides context, AI suggests, the teacher decides, the system records. At every step, the teacher is in control. AI is a thinking partner, not a decision-maker.
Teacher describes
Baseline data, assessment results, student context
AI suggests
Goal language, improvements, flags
Teacher reviews
Considers fit for this specific student
Teacher decides
Approves, modifies, or rejects
System records
Full audit trail of every interaction
Goal suggestions.
Teacher enters baseline data. AI suggests measurable criteria, realistic timelines, and strength-based language. Teacher modifies or approves. System validates completeness before saving. Goals are better and faster — 30 minutes instead of 90.
Present level insights.
AI analyzes assessment data and generates plain-language summaries of where the student is and what instructional implications follow. For uploaded IEPs, it works with parsed data to suggest improvements — it doesn't replace the evaluator's narrative.
Progress summaries.
At annual review, AI synthesizes 12 months of progress data into a quantified summary with trend analysis and recommendations (continue, modify, or discontinue). Teacher reviews and decides. Summary publishes to the parent portal in plain language.
Bias detection.
AI screens for deficit language, low expectations, compliance-focused goals without academic growth, and accommodation patterns that differ across peer groups without documented rationale. Flags are suggestions — the teacher always decides whether they apply.
No autonomous IEP generation.
Nothing is committed to an IEP without a human reviewing and approving it.
No student PII sent to external AI.
Names, IDs, test scores, and disability information never leave your district's infrastructure.
No replacing professional judgment.
If a teacher disagrees with an AI suggestion, the teacher wins. Always.
No black-box decisions.
Every AI suggestion is visually marked, fully auditable, and explainable.
AI-assisted content is visually marked with an AI-Assisted label. The audit trail records the original teacher input, the AI suggestion, the teacher's decision (approved, modified, or rejected), and a timestamp.
For federal or state audits, due process hearings, or parent review: the complete record of how every AI-touched element entered the IEP is documented and exportable. This is what responsible AI looks like — not a disclaimer, but a system designed so the proof is built in.
Your teachers are already using AI. The question is whether it's FERPA-safe, auditable, and under their control. We'd like to show you what that looks like.