AI Deployment Program · Education
Learning platforms and AI that students and educators actually use
Live classes, hands-on labs, progress analytics and AI tutors, built for student data and exam-day traffic from the first sprint.
We've shipped two learning platforms: an online learning platform for a US education company, and a hands-on cloud lab platform for an IT certification training provider.
Who it's for
Who this is for in education
For school groups, universities, training and certification providers, corporate L&D teams and education companies whose courses, live classes, grades and progress sit in separate tools, so struggling learners surface too late.
What we hear
The problems we hear most
And what we'd build for each one.
Fragmented tools
Courses, live classes, files and grades live in separate apps.
One learning platform
Too many roles
Students, instructors, admins and schools each need a different view.
Role-based portals
No view of progress
Teachers find out a student is struggling after the exam, not before.
Learning analytics and at-risk alerts
Manual admin
Enrolment, access and reporting run on spreadsheets and email.
Admin automation
Scheduling chaos
Classes, labs and cohorts across time zones and sections.
Scheduling and notifications
Assessment overhead
Setting, marking and tracking tests eats instructor time.
Automated and AI-assisted assessment
Engagement drop-off
Self-paced learners stall and quietly stop logging in.
Live classes and early warnings
Scaling delivery
A pilot cohort works; exam day for every learner doesn't.
Scalable SaaS architecture
What we build
What we build for education teams
Each capability is labelled with its evidence: shipped in this sector, built in another industry, or a core capability we offer.
- Shipped in education
Live online classes in the browser
WebRTC classes with camera, mic, screen share, raise hand and chat.
US online learning platform case study - Shipped in education
Student portals and instructor dashboards
Today's classes, schedules, section progress reports, at-risk filters and a grading queue.
US online learning platform case study - Shipped in education
Knowledge Hub
Notes, recordings, assignments and reference books, searchable.
US online learning platform case study - Shipped in education
AI tutor and at-risk prediction
An AI tutor, machine-learning at-risk prediction, AI-assisted grading and study recommendations.
US online learning platform case study - Shipped in education
Hands-on lab platforms
Real cloud environments launched from the browser, with scored hands-on assessments, for an IT certification training provider.
- Shipped in education
LMS integration
Connections into existing learning management systems through LTI, plus single sign-on.
- Built in another industry
AI tutors and voice avatars
Avatars that explain, quiz and answer in real time.
UK real-time AI avatar case study - Built in another industry
Agentic content automation
Agents that research, draft and check lessons, quizzes and notes, for an educator to review.
- Core capability
Mobile learning apps
Learning apps for iOS and Android.
Related work
Work you can ask us about
- US online learning platform case study
Student and instructor apps, live classes, an AI tutor and at-risk prediction.
- UK real-time AI avatar case study
A real-time avatar that answers from the client's own knowledge.
Before you sign
What your IT, security and compliance teams will ask
- Where does student data live, and who sees it?
- On your cloud or ours. Students, instructors and admins see only what their role needs, behind SSO (SAML or OIDC), MFA and session controls. In a multi-school or multi-client setup, each one is kept isolated.
- Is it auditable?
- Yes. Grade changes and admin actions are logged, and every AI action carries an audit log.
- Does a person stay in charge of grades and interventions?
- Yes. The at-risk model flags students and AI suggests grades and next steps. Instructors decide and act.
- Will it work with our LMS and sign-on?
- Yes. We've shipped LMS integration through LTI and single sign-on through SAML and OIDC, plus video, email, SMS and push, payments and CRM. Your exact integrations are scoped with your team in discovery.
- FERPA, COPPA or GDPR?
- Requirements such as FERPA, COPPA or GDPR are scoped with your team at kickoff, and the architecture is designed to support them. Certification stays with your organisation.
- Exam-day load and recovery?
- Built to auto-scale for exam days and cohort launches, with scheduled backups and tested restores.
- How are scope and price fixed?
- A Blueprint agrees the use case, data model, integrations, AI models, hosting and a cost estimate first. The build then runs at a fixed scope and price agreed in writing. No hourly billing.
- How long does it take?
- It depends on scope and data readiness. You get a written plan with milestones before any build starts.
- What happens after launch?
- New cohorts, courses and AI features as you grow, with monitoring, a monthly health report and safe changes, one request at a time.
How it runs
Scan. Blueprint. Build. Run.
The same pipeline as every TechTose engagement, scoped to your organisation.
- 01
Scan
We review your app, code or idea and send a written report.
Signed off by a TechTose architect. - 02
Blueprint
Your architecture decided and agreed: data model, backend, logins and roles, integrations, AI setup, hosting.
Signed off by a TechTose architect. - 03
Build
Built to the Blueprint, at a fixed scope agreed in writing.
Signed off by a TechTose architect. - 04
Run
Monitored, maintained and improved after launch.
Signed off by a TechTose architect.
Agents speed up the work. They don't make the decisions. A TechTose architect reviews every finding, plan and change before it reaches you.
Confidential by default
How we handle confidential work
- We sign your NDA before you share code, data or plans.
- Your code and accounts are yours. We work inside them, and our access ends when the work does.
- We never name a client, product or person publicly without written permission.
- We describe the work, not the client, as we have on this page.
Good first projects
- AI features for an existing learning platform
- Platform modernisation
- Platform scaling
- A full product build to a Blueprint
Bring to the call
- The learning problem you want to solve
- Who will use it: students, educators, admins, schools
- The systems it needs to connect to (LMS, SSO, payments)
Related reading
Guides for education teams adopting AI
Education AI deployment: questions
How can AI spot students who are falling behind?
A machine-learning model reads attendance, assessment scores and engagement and predicts who is at risk, so instructors can step in before an exam rather than after it.
Can an AI tutor answer from our own course material?
It can be built to answer from your notes, books and recordings using retrieval, as our avatar work answers from a client's own knowledge base. Instructors stay in the loop.
Can learners practise on real cloud environments?
Yes. We've built a hands-on lab platform for an IT certification training provider, where learners launch real cloud environments from the browser and are scored on hands-on tasks.
Do students need a separate video app for live classes?
No. Classes run inside the browser, with camera, mic, screen share, chat and questions in the same platform.
Is student data used to train AI models?
No. AI providers are set up on business or enterprise terms where your inputs aren't used for training, with data retention turned off wherever the provider allows it.
Why isn't the education client named?
We sign NDAs, and we never name a client, product or person without written permission. On a call we can walk you through the work, within what each NDA allows.
How does an education engagement start?
A short call to map your learning journey and decide whether a prototype is the right first step, then a Blueprint before anything is built.