Why Schools Choose EdTech AI
With 20+ years of software excellence, our team combines deep edtech software development experience with production-ready AI agents for education, delivering measurable outcomes across grading, analytics, and adaptive learning.
Impact: Our custom education software development services are tailored for every institution’s unique goals—whether you need to build a scalable e learning platform, integrate intelligent grading into your LMS, or implement a data-driven EdTech AI engine for personalized feedback.
Result: We don’t just build apps—we create AI-powered learning ecosystems that accelerate grading, improve student engagement, and enable smarter decision-making. Whether you need a learning management system, adaptive testing module, or AI-driven virtual tutor, Plavno is your trusted e learning software development partner for building future-ready EdTech AI solutions.
Key Challenges in Modern EdTech and Education AI
Rubric drift & Subjectivity: Instructors often apply grading rubrics inconsistently across sections or courses. Our AI agent for education ensures standardized scoring, rubric version control, and transparent reasoning—core to every custom education software development project we deliver.
Multi-Modal Submissions: Modern learners submit diverse content—text, code, math, LaTeX, diagrams, even oral responses. Traditional systems struggle with this variety. Our e learning software development team builds multi-modal recognition pipelines that handle complex input formats across languages and subjects.
Policy Alignment: Academic rules differ across institutions. Our education software development framework encodes policies for late submissions, extensions, plagiarism, and accommodations—ensuring automated grading remains fully compliant with academic integrity standards.
Explainability and Transparency: A key limitation of generic AI models is the inability to explain why a grade was assigned. With RAG-grounded feedback, our EdTech AI solutions justify every score, showing links to the exact course material, rubric, or example used—supporting fair grading and institutional accountability.
LMS Fragmentation: Most organizations rely on multiple LMS systems—Canvas, Moodle, Blackboard, Google Classroom, and more. Our custom e learning software development process delivers seamless interoperability through API-based LMS connectors and universal grading schemas.
Privacy & Compliance: Handling student data demands full trust. Plavno’s education AI adheres to FERPA, GDPR, and CCPA standards, ensuring data residency, role-based access, and end-to-end encryption throughout grading pipelines.
LLM Risks: Generic AI models may produce biased or ungrounded feedback. Our AI agents for education use retrieval-augmented generation (RAG) to mitigate these risks—ensuring every answer is validated against institution-approved knowledge bases, policies, and examples for factual accuracy and fairness.
AI-driven development
Solution
An agentic grading service with RAG-grounded evaluation and human-in-the-loop controls
Product Highlights
Agentic grading service with Retrieval-Augmented Generation (RAG)-grounded evaluation
RAG Knowledge Graph indexing rubrics, policies, exemplars, keys, lecture notes, references per course / assignment
Specialized evaluators for essays, code, math, and oral / audio work
Explainable scoring with per-criterion points, feedback citing rubric and course documents
Confidence and abstention flags routing ambiguous cases to human TAs with rationale
Fairness & calibration ensured via periodic gold-set calibration, drift detection, auto-alerts
Seamless LMS integration with grade posting, annotated feedback PDFs, regrade workflow support
Governance & security including FERPA compliance, role-based access, immutable logs, scoped retention
User Flows
Index course content and evaluation materials in RAG knowledge graph
Student submits assignment (essay, code, math, oral)
Specialized evaluator scores assignment using rubric and knowledge graph references
Scoring engine generates explainable scores, annotated feedback, improvement tips
Low-confidence or ambiguous cases flagged and routed to human TA with explanations
Human TA reviews flagged cases and finalizes scores / feedback
Grades and feedback posted back to LMS with provenance and audit trail
Students view scores, feedback, citations, and improvement guidance
Experience & Scale
Hybrid human-AI evaluation ensuring quality, fairness, and scalability
Transparent scoring enabling trust through citations to rubric, policies, examples
Supports multiple input types: text, code, math, oral / audio with tailored grading criteria
Scalable architecture indexing diverse course materials for fast, context-aware retrieval
Continuous model calibration and drift detection maintaining grading consistency
Secure, FERPA-compliant data management with role-based access and audit logs
LMS integrations enabling seamless adoption in educational institutions
Improves grading efficiency while preserving educator oversight and student engagement
