EdTech & Corporate Learning
EdTech Software Development — LMS, AI Tutors, Skills Assessment & Corporate L&D
EdTech is in the middle of an AI rewrite — the products that win will be the ones whose AI is pedagogically sound, not just demo-good. We build LMS, AI-tutoring, and corporate-learning platforms that respect learners and survive a procurement review.
What we hear from EdTech & Corporate Learning teams
- Off-the-shelf LMS that learners route around because the UX is from 2008
- AI-tutor products that confidently mis-explain a concept — and the K-12 buyer never trusts the product again
- Procurement reviews that surface FERPA / COPPA / GDPR-K gaps the team didn't know existed
- Corporate L&D platforms with content libraries nobody can find anything in
- Skills-assessment products with weak validity evidence — and an enterprise buyer who asks for it
- Accessibility (WCAG, Section 508) treated as a post-launch fix instead of a constraint
Regulation & compliance we work with
FERPA (US student data)
COPPA (US under-13)
GDPR + GDPR-K provisions (EU minors)
State student-data privacy laws (CA SOPIPA, NY Ed Law 2-d, IL SOPPA, etc.)
Section 508 + WCAG 2.2 AA (accessibility, mandatory for many public-sector buyers)
SOC 2 Type II
ESSA evidence tiers (where products make efficacy claims)
What we deliver
LMS replacement + custom-LMS builds with learner experiences people actually use
AI-tutoring platforms with retrieval grounding, scope guardrails, and pedagogical validity built in
Skills-assessment platforms with item-banking, validity-evidence workflows, and item-response-theory scoring
Corporate L&D platforms: content management, learning paths, microlearning, manager dashboards
Accessibility-first UI (WCAG 2.2 AA from sprint 1, not bolt-on)
Content-licensing workflows + DRM where rights-protected materials flow
Integration with SSO (SAML/OIDC), SIS (Clever, ClassLink, OneRoster), and HRIS for corporate L&D
FAQ
- How do you design AI tutors that don't mis-explain?
- Pedagogical scope, retrieval grounding, refusal behaviour, and a continuous evaluation harness. The tutor only answers from a known content corpus, refuses to wander outside scope, and is evaluated weekly against a labelled question bank with subject-matter-expert review of low-confidence outputs. We treat AI-tutor quality as a continuously measured product property, not a launch checkbox.
- Are you familiar with FERPA, COPPA, and state student-data privacy laws?
- Yes — and they're design constraints, not late additions. Student PII gets a separate data classification, retention policies are explicit, parental-consent workflows are first-class, and sub-processor inventories are kept current. For state-by-state laws, we maintain a compliance matrix that maps requirements to platform controls.
- Can you handle accessibility from the start (WCAG 2.2 AA / Section 508)?
- Yes — and it's a sprint-1 concern, not a launch-week fix. Components are built accessible from the design system up, automated accessibility tests run in CI, manual screen-reader testing happens before each release, and the VPAT is maintained as a living document. Many public-sector and enterprise buyers won't even start procurement without it.
- Do you build content / DRM workflows for licensed materials?
- Yes. Rights-protected content (textbooks, video courseware, assessments) needs licence-aware delivery, watermarking, expiry, and audit logs. We've built these workflows for both K-12 and higher-ed content publishers, and for corporate L&D platforms with third-party content libraries.