We're building the infrastructure layer for AI-ready organizational knowledge.
Every AI tool is only as smart as the context you give it. contxtmd exists because that context — for most organizations — is fragmented, stale, and not in a shape any AI can use. We fix that.
The thesis
Organizations have the knowledge. They lack the infrastructure to make it AI-readable. We built that infrastructure after watching the same pattern repeat across five real deployments — a research university, a startup operating studio, a hospital IP portfolio, a university innovation center, and a fintech ecosystem institute. Each required taxonomy-first structuring before any AI tool could be useful against their own data.
The approach
contxtmd is a horizontal platform with vertical applications on top. The platform handles multi-format ingestion, semantic enrichment, auto-taxonomy generation, and AI-ready export. The vertical applications ship the platform pre-shaped for startups, universities, innovation hubs, and specialized enterprise functions — so buyers get time-to-value in weeks, not quarters.
The portfolio
We're building multiple vertical applications in parallel, learning what's common across them and folding those learnings back into the engine. Specific product names stay off this site during the v1 launch — we're selling the platform and the vertical, not the inventory. Individual applications will be revealed as they reach public-launch quality.
The team
Founded by operators who've shipped the methodology across live organizations. Engineering-first. Committed to an open Context Transfer Protocol so the structured-context ecosystem is portable, not locked to one vendor.
Want to talk?
Whether you want a pilot, a custom build, or an API integration, it starts with a conversation.