EdTech & Learning AI solutions.

EdTech AI solutions for tutoring, feedback and assessment, inside learning platforms that work for every student, on every device, at exam-day load.

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What makes EdTech AI hard.

The EdTech AI challenges we design for before any code is written, so the AI holds up with real users, real data and real auditors.

Safe AI for students

Tutors and feedback tools need content guardrails, age-appropriate answers and teacher oversight before they reach a classroom.

Student data

Minors' data demands careful consent, retention and access controls, including what is ever sent to a model provider.

Accessibility by default

Keyboard, screen-reader and captioning support built into the component library, not retrofitted.

EdTech AI solutions we build

The AI use cases we build for EdTech teams, and the software platforms they run on. Each starts from a measurable goal, passes an eval gate before launch and reaches users through a gradual rollout.

The model work comes from our LLM and AI agent development team, tested by QA and AI evaluation. For results in production, browse our AI case studies.

Compliance we plan for

WCAG 2.2 AA
FERPA-aware design
GDPR

✓AI tutoring and study assistants
✓Automated feedback and grading support
✓Assessment and proctoring tools
✓Learning management platforms
✓Video and content delivery
✓LTI and SIS integrations

EdTech AI development services.

The WAMO Labs services most EdTech AI engagements draw on, from LLM integration to the platform around it.

AI integration

Our AI integration services put LLM applications, AI agents and RAG systems into the products and workflows you already run. Measured by evals, guarded in production, with a cost per request you can predict.

Custom web

Custom web application development for fast, AI-ready platforms that scale with traffic, data and your team. Copilots, smart search and clean APIs are part of the architecture, not a bolt-on.

UI/UX design

UI/UX design for AI products people trust: clear sources, easy correction, honest loading states, accessible by default. We design with engineers in the room from day one.

Questions about EdTech AI projects.

Timelines, cost drivers and compliance, answered plainly. More on how we build and evaluate AI in our AI engineering insights.

Which EdTech AI use cases do you build?

EdTech AI projects we build include AI tutoring and study assistants; automated feedback and grading support; and assessment and proctoring tools. Each one ships with a versioned eval set, guardrails and a gradual rollout, on the platform work listed above.

How long do EdTech AI projects take?

Most engagements start with a four-week immersion. By week 3 a first slice is live behind a feature flag for a small share of users, evaluated and instrumented. By week 4 you have a quarter-by-quarter roadmap with named owners. Full timelines depend on scope, integrations and compliance review.

What drives the cost of EdTech AI solutions?

Four things: the systems we integrate with (your LMS and SIS, usually over LTI), the compliance scope (WCAG 2.2 AA, FERPA-aware design and GDPR), how much evaluation and human review the use case needs, and inference volume, because cost per request compounds with usage. We size all four during the four-week immersion, so you know what it costs to keep going before you commit to a roadmap.

How do you handle compliance and data privacy in EdTech AI?

We plan for WCAG 2.2 AA, FERPA-aware design and GDPR from the first sprint and decide which data may ever reach a model provider before anything is built. Every AI feature ships with access controls, an audit trail and human review wherever a wrong answer carries real risk.

Building AI in EdTech & Learning?

Tell us the AI use case or product you're working on. We respond within one business day, with a real human and a real opinion.

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