EdTech engineering capabilities
We speak the standards your customers run on.
AI features in education only work when they fit the LMS, SIS, rostering and sign-in systems schools already use. These are the standards and practices we design every EdTech build around.
Standards and systems
Integration work we build into your product.
Each is an integration service we scope in the Product Review and deliver in your codebase. We list standards, not client names.
| Area | Standards | What it enables |
|---|---|---|
| LMS integration | LTI 1.3 / LTI Advantage (deep linking, assignment and grade services, names and roles) | Launch an AI feature from inside Canvas, Moodle, Blackboard or D2L, pick content into a course, and write scores back to the gradebook. |
| Rostering | OneRoster 1.2, Clever, ClassLink | Classes, enrollments and roles arrive from the district's source of truth, so the AI only sees the classes a teacher actually teaches. |
| Student information systems | Ed-Fi, SIS vendor APIs | Read the records a feature needs, at the permission level the user already has, without copying the SIS. |
| Learning records | xAPI, cmi5, SCORM 1.2 / 2004 | Record practice sessions, scores and completions in a learning record store or the LMS, in a format customers already report on. |
| Sign-in and provisioning | SAML 2.0, OpenID Connect, SCIM | Single sign-on with the institution's identity provider and automatic account provisioning and removal. |
| Content and assessment | QTI, Common Cartridge, CASE | Import and export questions, course packages and standards alignments so AI-drafted content fits existing libraries. |
| Accessibility | WCAG 2.1 AA, Section 508 | Keyboard use, contrast, labels, captions and screen-reader testing on every new screen, ahead of ADA Title II deadlines. |
| Privacy design | FERPA, COPPA, state student-privacy laws | Data minimization, institution isolation, age-appropriate design for users under 13, and no training on student data. |
How the team works
One team across product, AI, platform and quality.
A named lead engineer, US-hours overlap and two-week sprints from the first Product Review to production.
Product and learning design
Business analysts who map teacher, learner, admin and parent workflows before anything is built, and design AI that saves work people already do.
AI engineering
Retrieval with citations, voice and real-time AI, document extraction, text-to-SQL and agents with approval steps, evaluated on test sets your team reviews.
Platform engineering
Multi-tenant SaaS, role-based access, Stripe billing, cloud on AWS, Azure or GCP, and CI/CD with approval gates.
Quality and accessibility
Regression testing, accessibility testing and release management, so AI features ship without breaking what already works.
See one module on your own product.
Bring one product, workflow or AI initiative. In 30 minutes we pick the module that fits first, what it would cost to serve and what your customers' security review will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.