Series · 8 parts
Building SemanticStudio
A production-oriented series on building an enterprise RAG and multi-agent system.
In this series
All writing- SemanticStudio: A Production-Ready Enterprise RAG Agent SystemOpen-sourcing the multi-agent chat platform I built to test my AI-native architecture ideas. 28 domain agents, 5 configurable modes, 4-tier memory with Context Graph, GraphRAG-lite, and everything enterprises need to build production AI.
- The Chat Experience: Sessions, Folders, Files, and MoreA complete walkthrough of SemanticStudio's user-facing features—from session management to file uploads to power user shortcuts.
- Domain Agents: Specialization at ScaleWhy SemanticStudio uses specialized domain agents instead of one general-purpose assistant, and how to configure and manage them—from 12 to 50+ agents.
- RAG Chain Configuration: Models, Modes, and Fine-TuningThe power user's guide to configuring SemanticStudio's RAG chain—multi-provider LLM support, mode parameters, and full control over cost vs. quality.
- Memory as Infrastructure: The Complete 4-Tier SystemA deep dive into SemanticStudio's 4-tier memory architecture—working context, session memory, long-term memory, and the Context Graph. Progressive compression meets knowledge bridging.
- GraphRAG-lite: Beyond Vector SimilarityHow SemanticStudio's knowledge graph and entity resolution enable relationship discovery that pure vector RAG misses.
- ETL & Agent Creation: Growing Your Multi-Agent SystemHow SemanticStudio's self-learning ETL pipelines ingest data, build knowledge graphs, and automatically create new domain agents.
- Production Quality: Evaluation, Observability, and TrustWhat separates demos from deployable systems—SemanticStudio's quality evaluation, hallucination detection, and enterprise observability.