May 20264 min read
On building AI systems that actually fit how people work
Most AI integrations fail not because the model is wrong, but because the workflow design never accounted for how real work moves. Here's what we've learned.
AI Studio
phdstudios
.tech
Building the AI layer between ideas and outcomes.
Selected work
01
Live POC
Regulated Industry Decision Assistant
Agentic RAG pipeline for compliance research — hybrid retrieval, graph enrichment, and autonomous evaluation delivering authoritative answers at production accuracy.
60%
benchmark win rate
+50%
source diversity gain
zero
hallucinated answers
LangGraphQdrantVoyage AINeo4jGemini
02
In Production
Autonomous Operations Stack
Self-hosted agent system running in production daily — n8n workflows, Claude agents, and local LLM routing that capture, classify, and synthesize scattered inputs into structured briefs with zero manual touch.
n8nClaude AgentsOllamaSlackDocker
03
In Progress
Artist Portfolio Platform
Commissioned gallery site for a working artist — image-first design, fast static delivery, and a commerce-ready architecture built to add print sales without a rebuild.
Next.jsDesign SystemClient Work
04
Upcoming
Global Architecture Explorer
An interactive interface for exploring and navigating complex architectural systems at scale. Built for clarity at every level of zoom.
InteractiveVisualizationAI
Services
Journal
View all→PhD Studios builds AI systems that have to work in practice — workflow automation, retrieval pipelines, and interactive tools that move from idea to running in production.
We ship real systems and get better with each one.
RAG · Agents · Automation
core stack
Production
deployed systems
Full stack
API to UI