#dag

63-layer continuous-time Symplectic Neural ODE computing topological invariants of real market signals. 256-dim feature space with non-Abelian gauge field geometry. 27 data products (property intelligence, DAG manifold computation, federal contracts, distressed real estate) with autonomous Stripe purchase. 500K out-of-pocket validated embeddings. Free tier available.

Monitor and operate Dagster instances with AI agents. 19 tools for runs, assets, jobs, schedules, sensors, and instance health. Supports multi-environment, cross-version compatibility, and write operations (launch, terminate, reload).

Pedagogical word enrichment for AI agents. One API call returns what would cost 5 separate calls + an LLM generation: definition, IPA pronunciation, etymology as narrative, a teaching insight from Kelly (AI tutor), translations in 8 languages with native pronunciations, 3 age-appropriate explanations (kid/adult/senior), and a knowledge graph of connected words. Pre-computed and edge-cached on Cloudflare D1 — ~3ms response globally. Also includes 62,000 daily lesson segments across 365 days, 11 languages, and 3 age tiers. Built for tutoring agents, language learning apps, and educational chatbots. 6 tools: word_enrich, word_translate, word_connections, word_search, word_batch, lesson_of_day.

MCP-Airflow-API is a Model Context Protocol (MCP) server that transforms Apache Airflow REST API operations into natural language tools for LLM integration. Built for DevOps engineers, data engineers, and Airflow administrators who need intuitive cluster management capabilities.

The Neuro-Symbolic Autonomy Framework integrates neural, symbolic, and autonomous learning methods into a single, continuously evolving AI agent-building system. This prototype demonstrates the SCMA component, which enables AI agents to self-design new AI agents using Generative Architecture Models.