SLECapabilities

Personalize instruction. Differentiate teaching. Grade transparently.

ArthurAI™ School Learning Edition is built on the same agentic substrate as the other editions, configured for the realities of K-12 — under-13 cohorts, district-level rosters, parent-facing disclosure, and a teacher who is the decider, not the AI.

Talk to our team →Your day with SLE →
What it does
  • Personalized curriculum

    AI generates a curriculum your way.

    Start from your existing district scope-and-sequence or a fresh template. ArthurAI™ generates a personalized course schedule for each learner — subjects, weeks, days, lessons — using each student's Learning Cognitive Profile to adapt content complexity and style. The teacher reviews before students see it.

    How the LCP drives this →
  • Six-step lessons

    Every lesson follows a research-backed structure.

    Introduction → Key Concepts → Detailed Explanation → Practice Questions → Real-World Applications → Summary. Each step is generated on-demand against the lesson scope. KaTeX math and Mermaid diagrams are sanitized and validated before display.

    The 6-step lesson anatomy →
  • AI tutor

    A tutor that knows what the student is working on.

    Context-aware tutoring with student profile, learning style, current lesson, and conversation history assembled at every turn. Students can highlight any text in the lesson and ask 'Explain this' for an in-context answer. Tutoring is disabled during practice questions so it can't write the answer for the learner.

    How the AI tutor works →
  • Transparent grading

    Every AI-suggested grade is reviewable.

    Quiz sessions track every attempt with attempt numbering and completion transitions. Faculty analytics aggregate per student, per class, per assessment. The teacher attests every grade before it enters the academic record. AI is decision support; the teacher is the decider.

    Assessment architecture →
  • Multilingual classroom

    9 languages, including RTL.

    English, Arabic, Spanish, Urdu, French, Turkish, Swahili, Portuguese, Hausa. The AI tutor responds in the student's selected language. AI-generated curriculum can target any supported language. Document direction flips automatically for Arabic and Urdu.

    Language architecture →
  • Educator-attested workflow

    The AI reasons. The teacher decides.

    Every workflow surface where ArthurAI™ output reaches a student carries an educator-review checkpoint. AI-generated curriculum is teacher-approved before student access. AI-suggested grades are teacher-attested before they enter the gradebook. The disclosure surface is in-line, not a one-time consent.

    Disclosure language →
  • District operations

    Built for the way districts actually run.

    Bulk CSV upload for student rosters and teacher accounts. Sub-admin delegation with permission-scoped access (manage teachers, manage students, manage courses, view analytics, manage announcements, manage billing, manage settings). License-quota tracking per institution. Branded emails and certificates. Theme generation from a natural-language prompt.

    Multi-tenant architecture →
  • Engineered compliance

    FERPA, COPPA, AB-1791 — built in, not bolted on.

    ArthurAI™ operates as a school official under FERPA. For under-13 cohorts, the school-as-agent COPPA model authorized by the FTC handles parental consent. AI-disclosure language for districts subject to California AB-1791 and analogous state statutes is configurable at deployment. Audit trails are immutable-style and retention-aligned.

    Full compliance posture →
Try the LCP sampler

What the SLE asks every learner before the first lesson.

The real instrument is thirty questions across five categories. This sampler is a five-question slice — same dimensions, same posture, no flattery. Click through and see the signature.

LCP Sampler · 1 of 5Visual ↔ Verbal

You are learning how a heat engine works for the first time. The explanation reaches a point where the cycle’s phases compress and expand the working fluid. Which would help you understand faster?

Deeper on how it works

Eight more capability deep-dives, all code-true.

The complete how-it-works gallery →
Trust posture

FERPA · COPPA · ADA / Section 504 / 508 · WCAG 2.1 AA · AB-1791 — see the full compliance posture, security pillars, and data handling for procurement-grade detail.

The motto

The AI reasons. The teacher decides.

Talk to our team →See the deployment roster →