For content publishers
The AI layer for STEM content.
You have the catalog. You have the institutional relationships. Mika is the AI engine that embeds into your product — content-aware, deeply integrated, and built for STEM specifically.
The problem
Generic chatbots don’t know your curriculum. Point tools don’t talk to each other. Institutions buy three vendors and none of them integrate with the textbook the course was designed around. Publishers carry the content authority — but lose the AI-driven student layer to whoever ships fastest.
What we offer
Three ways Mika plugs into your catalog.
01Embedded deployment
Mika components run inside your existing product surface — embedded, not bolted on. Students get the AI tutor where they already are; you keep the relationship and the data.
02API access to the platform
The Cartographer router, the subject-native STEM models, gap detection, and assessment generation — exposed as a programmatic layer.
03Content-aware models
We co-train against your catalog so the AI references your textbooks, your worked examples, your problem sets — not generic web data.
How it fits
Your content, our engine, your students — in your product.
01
Your content
Textbooks, worked examples, problem banks, assessments.
02
Mika ingestion
Curriculum mapping, concept graph extraction.
03
Cartographer router
Routes each interaction to the right specialist model.
04
Your students
Personalized tutoring, feedback, gap detection — under your brand.
Partnership models
Two ways we work with publishers.
Integration
Mika components inside an existing product. You own the surface; we provide the AI layer behind it.
- Embedded in your authoring or learning product
- Single-tenant or shared deployment
- Co-developed reference integrations
Example — An AI tutor embedded inside one digital textbook product, sold as part of that title’s subscription.
Licensing
License the underlying engine for use across multiple products in your portfolio.
- Multi-product license terms
- Roadmap influence and early access
- Cross-product analytics
Example — The Mika engine embedded across a publisher's full STEM courseware portfolio, licensed for cross-product use.