SYNDI - Synthetic Intelligence for Data Integrity

Automated lab data capture enabling AI-ready data: AI extracts protocols, validates SOPs, collects compliant structured data

The Three Core Components:

1. 🤖 PAUL (Protocol Automation Librarian)

   • Automatically extracts Standard Operating Procedures (SOPs) and data elements from written laboratory protocols
   • Uses AI to parse unstructured protocol documents into structured SOPs

2. 🔍 SAM (SOP Authoring Manager)

   • Validates and optimizes SOPs extracted by PAUL
   • Provides a template-driven SOP authoring interface
   • Ensures SOPs comply with regulatory requirements

3. 📋 CLAIRE (Compliant Ledger-based Automation for Integrated Reporting and Export)

   • Electronic Lab Notebook (ELN) data capture system
   • Renders validated SOPs as dynamic tabbed forms
   • Collects structured lab data with full audit trails and provenance tracking
   • Supports instrument integration and prerequisite ELN data import

How It Works (Workflow):

SME writes Protocol → PAUL Extracts SOP → SAM Validates → CLAIRE Collects ELN Data → AI-ready Data for Analytics

Key Features:

• AWS-based deployment (Lambda, S3, Cognito, CloudFront, API Gateway)
• Regulatory compliance with immutable storage and full audit trails
• Role-based access control (Admins, Lab Managers, Researchers, Clinicians)
• FastAPI backend (Python) + React/TypeScript frontend
• Multi-organization support with environment-based configuration (dev/stage/prod)
• Data provenance tracking - complete lineage from protocol to final data

Primary Use Case:

Streamlines laboratory operations by converting written protocols into structured, validated forms that capture research data in an AI-ready format - making lab data immediately ready for analytics, reporting, and regulatory submissions.

Citation

If you use SYNDI, please cite the archived release:

Pathway Bio. (2026). SYNDI: Synthetic Intelligence for Data Integrity (v0.1.0-alpha) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.20829393