OntoAgent is an architecture and framework for developing and deploying embodied intelligent agents that rely on content (ontology and lexicon) to empower natural language interaction and decision-making. Unlike language models, OntoAgent does not rely on large opaque trained models that act as a black-box for decisions; instead, OntoAgent's knowledge and heuristics are fully inspectable, and traces and explanations of its decisions are available in natural language.

Dreamward is all about viewing your content as data, and using that view to automate layouts, rendering, and publishing. Using Dreamward's markup language, content is written in as close to natural language as possible, allowing you to focus on what matters most. Later, light markup or structure can be easily added to enable Dreamward to parse, organize, and publish. Custom rendering components and layouts make producing PDFs, cuttable sheets, and other products easy.