How It Works
Four pipelines power the HD Research Hub. All open source, all running on consumer hardware.
Daily Data Pipeline
Papers flow in from PubMed, get analyzed by LLM on Jetson, and populate the knowledge base that powers everything.
PubMed API
12 search queries
Full Text (PMC)
Open access papers
LLM Analysis
Gemma 4 on Jetson
Knowledge Base
1,571 chunks
Live Website
Auto-deploy via Vercel
Ask HD Research (Chatbot)
Questions in any language get translated, matched against full-text research, answered by Gemma 4 via Google AI Studio, and translated back.
Input
User Question
Any language
Detect
Sarvam AI
22 Indian languages
Search
Knowledge Base
1,571 full-text chunks
Inference
Google AI Studio
Gemma 4 (agentic + multimodal)
Translate
Response Back
User's language
Output
Cited Answer
With PubMed IDs
Experiment Pipeline
Hypothesis generation and drug repurposing scoring. Runs on the Jetson overnight.
Question
Pull Papers
LLM Analyze
Extract
Hypothesize
Score
Publish
Autonomous Agents
Four agents run on schedule, keeping the knowledge base fresh and hypotheses updated.
Paper Scout
Discovers new papers
Every 6hHypothesis Refiner
Re-scores drug candidates
DailySocial Watcher
Monitors X, Reddit, HN
DailyDigest Writer
Weekly research summary
WeeklyWiki Compiler
Compiles knowledge
After each runAuto-Publish
Git push triggers Vercel
InstantThe Self-Improving Loop
Experiments generate data. A wiki compiler organizes the findings. Those findings feed into the next experiment. Each cycle, the system learns from its own output and improves, without anyone having to restart from scratch.
Run Experiment
data/*.json
Wiki Compiler
wiki/ pages
Next Experiment
Every cycle, the wiki grows. 117 targets, 5 hypotheses, 4 experiments compiled so far.
Built With
Built by data scientists, not doctors. Nothing on this site is medical advice.