Structured asset
Value lives beyond individual pages in a versioned corpus, annotation schema and links between sentences, patterns and study sets.
Metkagram · partnerships and funding
Turn a research language corpus into a testable learning system.
Metkagram already combines annotated content, reusable patterns, a static API and mobile apps. We are looking for investors and partners to validate the method, scale editorial quality and expand to new languages—without inventing traction claims.
Discuss investment or partnership- 3,484
- reusable B2–C1 patterns
- 969
- annotated sentences
- 72
- curated document sets
- EN · DE
- learning languages
01 · Why this can compound
Why this can compound
Two product surfaces
The same material works as a learning interface for people and as machine-readable data for agents and researchers.
Static economics
The core site needs no runtime backend: publication is reproducible, maintenance stays lean, and content remains available on GitHub Pages.
Localization by contract
New languages can enter through shared fields, validators and English fallback rules instead of copied interfaces.
02 · What the next resources unlock
What the next resources unlock
- 01
Method validation
A preregistered pilot with comparison conditions, defined outcomes and a public report.
- 02
Editorial quality
Linguistic review, inter-annotator agreement and correction of weak or artificial examples.
- 03
New languages
A localization pipeline, language-specific rules and the first target language beyond English and German.
- 04
Learner retention
Personal paths, active retrieval and measurable return loops around useful patterns.
03 · Ways to participate
Ways to participate
Investment conversation
Discuss milestone funding, success measures, deal structure and the boundary of the open project.
Research partnership
Run a learning or NLP experiment on the corpus with a reproducible approach and clear attribution.
Content and expertise
Contribute editorial work, linguistic review, use cases or new language collections.
Technology partnership
Support API access, agent integrations, data-quality tooling, accessibility or hosting.
06 · Concrete pilot packages
Start with a small outcome, not a vague collaboration
Each format below can start as a bounded pilot with explicit deliverables, license boundaries and a success criterion.
- 01
University research pilot
For: Applied linguistics, SLA, NLP, learning-science groups
A versioned corpus, frozen stimuli, annotation schema, reproducible routes and a preregistration-ready research question.
Pilot outcome: Run one measurable study on annotation, transfer, retrieval or annotation quality and publish the result regardless of direction. - 02
Teacher-curated advanced topic pack
For: Advanced-English/German teachers, schools and serious language creators
A co-curated Pattern Atlas topic with printable/shareable cards, canonical links and visible reviewer attribution.
Pilot outcome: Produce one reference-quality topic pack that is useful in a real lesson and can earn natural teacher links and reuse. - 03
Learning-tool distribution pilot
For: H5P/LMS maintainers, Anki ecosystem, course platforms and educational tooling
A compact export of one reviewed study set with formulas, examples, translations, provenance and stable canonical URLs.
Pilot outcome: Make Metkagram content usable inside an existing learner workflow instead of requiring another standalone platform. - 04
AI tutor pattern-layer pilot
For: AI tutors, agent projects and developer tools that need reviewed language objects
Read-only intent, pattern, related-pattern and provenance retrieval through the public API/MCP layer.
Pilot outcome: Let an external tutor retrieve a canonical reviewed pattern and cite it instead of inventing a grammar explanation from scratch.
04 · What stays protected
What stays protected
- Core learning materials remain free to access.
- Sponsors do not receive the right to alter research findings, annotations or recommendations for their own interests.
- Partnerships and contributions are acknowledged transparently; data keeps its provenance and attribution.
- Audience, efficacy and revenue metrics are published only when they can be verified.
05 · Start with a concrete proposal
Start with a concrete proposal
Message MetalHatsCats on LinkedIn with who you are, the resource or expertise you can contribute and the outcome you want. We will reply with a suitable milestone, artifact and measure of success.