RAG Knowledge System
Turns a corpus into an interrogable knowledge system: ingestion, parsing, chunking, embeddings, vector storage, retrieval, context assembly, generation and citations.
- Embeddings
- Vector search
- LLM APIs
Source · soonDemo · soon
Mission profile
AI systems engineering: retrieval pipelines, knowledge and personality systems, and multi-agent orchestration. The Oracle is about building the system around the model, not just prompting one.
The portfolio here follows an arc: a RAG system that turns a corpus into an interrogable knowledge base, an instance generator that builds an AI around a subject, and a command center that routes work between specialized agents.
Arsenal
- Retrieval-Augmented Generation
- Embeddings & Vector Search
- LLM APIs
- Agent Orchestration
- Tool Use
- Prompt & Persona Design
- Python
- TypeScript
Projects
Quest board in the works
AI Instance Generator
Give it a subject and it discovers sources, builds a corpus and a RAG system, writes a behavioral system prompt, and produces an AI instance you can talk to.
- RAG
- LLM APIs
- Prompt design
Source · soonDemo · soonAI Command Center
A command center that analyzes a task, decomposes and routes it to specialized agents, then synthesizes their results, with tool use, state and memory.
- Agents
- Tool use
- Orchestration
Source · soonDemo · soon
Education
- Bachelor's in Software Engineering
- Master of Business Administration (MBA)
- Bachelor's in Global Business