Public Sector Radar
Ecosystem-level reports that make defaults, category leakage, and differentiation visible.
AI tooling sector analysis
We publish evidence-grounded Sector Radar reports that show the default patterns forming in AI tooling, where real differentiation survives, and what builders should understand before choosing or building.
Field Brief
A source-backed synthesis from three accepted public Sector Radar reports covering 78 public repositories across MCP memory, browser-extension starters, and IDE-native AI coding agents.
Latest publication
Our third public report analyzes 22 source-verified VS Code AI coding-agent extensions, mapping the IDE-agent default, protocol-client boundary, lineage signals, and Super Cluster bridge relevance.
Second publication
Our second public report analyzes 24 fork-and-build Chrome extension starter repositories, mapping a sharply converged MV3 + TypeScript + Vite + React default and the gaps still open for builders.
First publication
Our first report analyzes 32 repositories connected to MCP memory, separating primary MCP memory servers from adjacent infrastructure and mapping the cluster roles that define the sector.
Public posture
Diversum measures convergence patterns. It does not claim AI authorship, and it does not turn maintainers into targets. Public reports describe sectors; private audits help builders inspect their own work.
Ecosystem-level reports that make defaults, category leakage, and differentiation visible.
Voluntary repo or idea review for builders who want evidence-grounded convergence feedback before publication.
About
Diversum publishes evidence-grounded sector analysis for AI tooling ecosystems. Our interest is in mapping how open-source AI infrastructure converges, differentiates, and forms defaults.