"Most RAG projects don't fail because of the LLM. They fail because they treat PDF ingestion as a simple file upload. They hallucinate because they guess instead of verify."
I am an AI-Native Architect focused on the Ingestion Gap and Verifiable Truth. My mission is to replace "Digital Paper" (dead PDFs) with structured, semantic knowledge that allows Local AI to reason without hallucinations.
🏛️ Flagship Mission: PantheonRAG
The Consensus Engine for Mission-Critical Data.
Pantheon is not a chatbot. It is a scientific instrument designed to eliminate hallucinations through rigorous multi-agent debate and graph-based verification.
- ⚖️ Solomon Consensus Engine: Agents (Legal, OCR, Vision) must reach agreement before answering.
- 🔬 The Laboratory: A "Glasshouse" for radical transparency and auditability.
- 🧬 Surgical HITL: Precision tools for expert intervention in the reasoning chain.
I build modular, production-ready kits to fix the "Garbage In" problem for high-compliance environments (Public Sector / Enterprise).
- RAG Enterprise Core The Blueprint for BSI-compliant, self-hosted RAG. Features: Ingestion Triage, GraphRAG, Semantic Caching, and Full Observability. Status: Architecture Preview / Closed Source Engine.
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Validated Table Extractor The proof that RAG can handle complex tables if you use Docling + Vision Validation. Status: Open Source Audit Tool.
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Smart Ingest Kit Production-grade document ingestion pipeline using Docling v2. Solves: Layout Analysis, Table Reconstruction, Markdown Conversion.
- PantheonRAG-Mail A fully autonomous, privacy-first AI email assistant running locally The proof that my ingestion engine works in the wild DSVGO / CCPA compliant
I don't believe in "One Model Fits All". I believe in Triage and Tiers.
| Ingestion | Intelligence | Memory | Observability |
|---|---|---|---|
Docling v2 |
Qwen2-VL |
Neo4j |
LangGraph |
PyMuPDF |
Ollama |
ChromaDB |
Sentry |
Marker |
DeepSeek |
Redis |
Grafana |
- Structure > Vectors: Embeddings are useless if the input table was ripped apart
- Verification > Generation: Don't just generate text. Verify it against the source
- Local > Cloud: Data sovereignty (GDPR/BSI) is not optional. I build for air-gapped reality
- Logic > Magic: I prefer deterministic code for business rules over probabilistic LLM guessing
- Reddit: u/ChapterEquivalent188 - Discussing the "PoC Trap" & Ingestion Realities.
- Focus: Currently open for strategic dialogue regarding High-Compliance RAG Architectures (Public Sector / Industry).
- 2dogasandanerd - gmail.com My Agnets told me you said Hi