An AI-powered engine that scans your entire course catalog for accessibility gaps, missing content, and broken integrations, turning a weeks-long manual audit into a matter of minutes.
If you've ever tried to audit hundreds of courses manually, you know the drill. Open each one, click through every page, check for alt text, verify links, confirm the syllabus is there, make sure the LMS modules are actually working. Multiply that by hundreds of sections every semester.
Most institutions know their courses have compliance issues. The problem isn't awareness, it's bandwidth. Quality assurance teams are small, accreditation timelines are rigid, and by the time you finish reviewing everything by hand, half the courses have already been updated and need re-checking.
The institution I worked with was spending three full weeks every semester on this process. Faculty were frustrated by the back-and-forth, and the QA team was burning out. Something had to change.
Three full weeks of clicking through every course, every semester. The team could barely keep up.
Different reviewers applied different criteria. What passed one review might fail the next.
Repetitive, tedious work with no end in sight. The team was losing morale and people were leaving.
Deadlines don't wait. When accreditors come calling, you need proof that every course meets the standard.
Spent two weeks with the QA team observing their manual process, documenting every check they performed, and mapping those checks to accreditation standards. We identified 40+ discrete compliance criteria that the scanner would need to verify.
Built API connectors to pull course content directly from the LMS, pages, modules, assignments, media files, and metadata. Designed the pipeline to run incrementally so it only re-scans content that has changed since the last audit.
Developed natural language processing models to check for things rule-based systems miss: syllabus completeness, learning objective alignment, content quality scoring, and accessibility compliance beyond just alt text and link checks.
Created a reporting dashboard that gives QA teams an at-a-glance view of compliance status across every course, with drill-down capabilities and automated remediation suggestions that faculty can apply in a few clicks.
Let's talk about how an automated compliance solution could work for your institution.
Start a ConversationScans every course, module, page, and assignment across your entire LMS. No sampling, no guesswork, 100% coverage.
Checks for alt text, color contrast, heading structure, link functionality, and WCAG compliance automatically.
NLP analysis verifies that every syllabus contains required elements: objectives, policies, grading criteria, and institutional disclosures.
At-a-glance compliance status for every course, department, and college. Drill down from institution-wide to individual pages.
Auto-generates evidence packages for accreditation reviews, mapping every compliance check to the specific standard it addresses.
Sends targeted, actionable emails to faculty with exactly what needs fixing, along with one-click remediation options where possible.
A single view showing compliance scores across every department and course. Color-coded severity levels help QA teams prioritize their work, and trend lines show improvement over time.
Drilling into any course reveals every detected issue, categorized by type and severity. Each issue links directly to the affected page or module in the LMS for fast remediation.
One-click report generation that maps every compliance check to the relevant accreditation standard. Includes evidence screenshots, timestamps, and sign-off workflows.
We went from dreading accreditation season to feeling genuinely prepared. The scanner catches things we would have missed, and our faculty actually appreciate the specific, actionable feedback instead of vague 'your course needs work' emails.
The biggest wins came from the 40% of checks that still needed a human eye. The scanner surfaces the issues and provides context, but the QA team's expertise is what turns that information into actual quality improvement. Trying to fully automate everything would have produced worse results.
The first version of the notification emails was too clinical and felt punitive. Faculty were ignoring or pushing back. We rewrote everything to be helpful and specific, "Here are 3 things you can fix in 5 minutes", and suddenly remediation rates tripled. The tech didn't change. The communication did.
The original plan was to run full scans at the start and end of each semester. But switching to incremental, scanning only changed content as it's updated, turned a periodic audit into continuous monitoring. Issues get caught days after they're introduced, not months.
Every project starts with a conversation. Tell us about your compliance challenges and let's figure out what an automated solution could look like for you.
No pitch. No pressure. Just a conversation about what might work.