A minimal graph engine for grounded AI — records, associates, and retrieves, but never invents. Written in Rust.
Agent Capability Standard is an open specification for composable AI agent capabilities. It defines 36 atomic capabilities across 9 cognitive layers, a type-safe workflow DSL, and grounded world modeling with trust-aware conflict resolution. Built on the Grounded Agency philosophy, it makes agent reliability structural—not optional.
DeepVault Nexus is a local-first RAG platform for administering governed knowledge sources and building source-grounded AI experiences.
Corrective RAG with LangGraph: evaluates retrieval quality, routes to web search when needed, refines context, and generates grounded answers.
Self-RAG chatbot with LangGraph that retrieves from internal PDFs, verifies grounding (IsSUP), checks usefulness (IsUSE), and iteratively rewrites queries to improve answer quality.
The Autonomous, Grounded Hardware Diagnostic Engine. A multi-modal infrastructure for physical-world engineering.
A natural-language A2A information retrieval agent with bounded web research, grounded answers, specialized API routing, and a local CLI.
Instruction-following vision-language model (VLM): grounded text instructions executed via multi-modal reasoning
The Offline-Libby repository is a fully offline, air-gapped AI knowledge assistant designed for high-integrity information retrieval. It allows users to turn local document folders into a private, conversational knowledge base without any cloud dependency.
C7 — A Two-Hemisphere Grounded Cognitive Architecture
Agentic entity search engine that converts natural language queries into source-grounded entity tables using web search, scraping, LLM extraction, evidence verification, deduplication, ranking, and observability.
Findings — live AI data analysis (findings.site). TokenTrim — leaner prompts, lower token cost (WIP). Full-stack + grounded LLM apps by Asra Saeed.
A portfolio of practical AI projects demonstrating retrieval, grounded synthesis, evaluation workflows, and production-ready AI application patterns.
TraceRAG is a citation-first RAG system that retrieves answers at sentence-level precision with exact verbatim grounding and structured source traceability.
Full-stack knowledge operations platform for owner-scoped notes, retrieval-ready indexing, grounded answers, and persisted evaluation workflows.
Grounded multi-agent biomedical research and due-diligence agent. No citation, no claim - every finding traces to a real record (PMID, NCT, patent no.) and is verified by a decorrelated model. Runs locally on Ollama, no API key required.
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