#WarpHelix Technical Architecture & Security

From Stanford's Biomni to enterprise-grade product

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#Foundation: Stanford Biomni

Biomni is Stanford's first general-purpose biomedical AI agent framework, featuring two core innovations:

#Biomni-E1: Unified Biomedical Environment

Through Action Discovery, Biomni systematically mines tools and databases from thousands of papers, creating the first unified agent execution environment for biomedicine.

10,000+ biomedical papers
         ↓ Action Discovery
150+ tools + 59 databases + 105 software packages
         ↓ Unified interface
Biomni-E1 Unified Environment

#Biomni-A1: Generalist Agent Architecture

• LLM reasoning — Understands questions, plans analysis strategies
• Retrieval-augmented planning — Finds optimal tool combinations
• Code execution — Auto-generates and runs analysis code
• Iterative refinement — Checks results, auto-adjusts approach

#WarpHelix Architecture Overview

┌─────────────────────────────────────────┐
│              User Layer                  │
│  Web UI  ←→  WebSocket Real-time        │
├─────────────────────────────────────────┤
│          Application Services            │
│  Auth │ Metering │ Sessions │ Files      │
├─────────────────────────────────────────┤
│            AI Agent Layer                │
│  LLM Reasoning ↔ Tool Discovery ↔ Code  │
│         Retrieval-Augmented Planning     │
├─────────────────────────────────────────┤
│         Biomni-E1 Environment            │
│  150+ Tools │ 59 DBs │ 105 Packages     │
├─────────────────────────────────────────┤
│           Infrastructure                 │
│  LLM API │ Database │ Storage │ Sandbox  │
└─────────────────────────────────────────┘

#AI Agent Core Workflow

User Question
    ├── 🧠 Think — Understand intent, plan analysis
    ├── 🔍 Search — Retrieve relevant tools from 150+
    ├── ⚡ Execute — Generate and run code in sandbox
    ├── 👁️ Observe — Validate results, iterate if needed
    └── 📋 Solution — Synthesize report + visualizations

#Retrieval-Augmented Planning (RAP)

1. Tool Retrieval — Vector search for relevant tool documentation
2. Context Injection — Feed tool docs, usage examples into LLM context
3. Plan Generation — LLM produces precise analysis plan with full context
4. Execution Validation — Verify each step, adjust as needed

Benefit: Even if the LLM hasn't "memorized" a specific bioinformatics tool, it can retrieve accurate documentation — drastically reducing hallucinations.

#Security Sandbox

#🔒 Data Security & Compliance

#Data Flow

User Input → HTTPS → WarpHelix Server
    ├── Conversations → Encrypted DB (user-isolated)
    ├── Files → Encrypted storage (user-isolated)
    ├── Code → Secure sandbox execution
    └── LLM calls → AWS Bedrock / DashScope
                     (no storage, no training)

#Security Commitments

#Compliance

• GDPR — Data access and deletion rights supported
• China Classified Protection — Private deployment meets requirements
• Institutional audits — Comprehensive audit logs

#Deployment

Docker Compose one-click deployment:

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#Contact Us

• 📧 Email: peirongw@foxmail.com
• 🌐 Website: website.autoinfra.cn