Pyxon-Eye LMS Grading for Moodle

Developed for

Universities, training providers, and EdTech teams that need private, on-prem AI grading inside Moodle (and similar LMS) without cloud dependency

The challenge

Manual grading of open-ended LMS questions does not scale for large cohorts
Cloud LLM grading breaks data residency and campus network constraints
Limited GPU servers cannot host frontier models for continuous exam workloads
Bulk “grade everything at once” approaches overload small GPUs and hide per-question feedback quality

The Solution

A Pyxon-Eye–powered LMS integration that plugs into Moodle for grading and analysis. Work is scheduled question-by-question on Pyxon SLLM so a modest GPU box stays within VRAM and thermal limits while teachers get structured scores and explanations per item.

Key capabilities include:

◇ Moodle-oriented hooks for assignment and quiz grading workflows
◇ Question-by-question inference queue tuned for small GPU footprints
◇ Pyxon SLLM as the local grading backbone (offline / on-prem)
◇ Pyxon-Eye analysis views for cohort patterns, weak topics, and grading consistency
◇ Fits constrained lab or campus machines without hyperscale hardware

Impact

Brings private AI grading and learning analytics into Moodle on hardware institutions already have—without sending student answers to the public cloud.

Organization benefits:

Faster turnaround on open-response grading
Per-question feedback instead of opaque bulk scores
Data stays on campus or institutional servers
Reuses PYXON Labs SLLM and GPU Lab capacity guidance

Meet Our PIs

Discover the principal investigator behind this project and the expertise that made it possible.

Hamza Salem

Head of PYXON Labs

Leads PYXON Labs research across Arabic AI, edge systems, governance, and applied products that ship into real environments.

// Open Vacancies

Join as a Scientist

Join our team working on Pyxon-Eye LMS Grading for Moodle. Explore opportunities in machine learning, Arabic NLP, computer vision, edge systems, and applied AI research.

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Apply to this project

Submit the same scientist application used on PYXON Labs — tell us about your CV and how you’d contribute to Pyxon-Eye LMS Grading for Moodle.

Or email info@pyxon.com

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