Abstract
Current artificial intelligence (AI) systems can generate semantically relevant markdown responses, but they do not reliably generate high-quality interactive user interfaces. Techniques described herein address that gap through a two-layer downstream enrichment system that transforms arbitrary AI-agent markdown into rich user interface components without modifying the originating model. Layer 1 is a deterministic, data-shape-aware pipeline that converts markdown blocks into charts, Key Performance Indicator (KPI) cards, tables, and titled sections using specific routing and absorption heuristics. Layer 2 is an optional AI presentation layer that enhances the structured output through semantic highlighting, chart refinement, thread-context-aware adaptation, and layout optimization, without altering the underlying content or data.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Doshi, Bhautik Kishorchandra; Goho, Mark; Lovoy, Zac; Pontaza, Juan Carlos; and Mehta, Arpita, "AI OUTPUT ENRICHMENT SYSTEM WITH DATA-SHAPE-AWARE ROUTING, ENRICH DIRECTIVE PROTOCOL, AND CONTEXT-AWARE BLOCK ABSORPTION", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10362