Laboratory Quality & Compliance Automation
Deploys a mission-based agentic AI system with six specialized agents that can execute multiple mission types: reagent recall impact analysis, QC investigation with Westgard rule evaluation, comprehensive compliance audits against CAP checklists, risk assessments, and inspection preparation packages. The system provides autonomous decision-making with human approval gates, predictive compliance insights, and self-healing capabilities.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Mission Control Interface - Mission type selection and configuration for compliance analysis workflows
Agent Orchestration View - Multi-agent network coordination with live reasoning traces and execution DAG
Execution Timeline - Detailed performance metrics, token usage, and step-by-step workflow tracking
Results Dashboard - Comprehensive findings with reagent recall impact analysis and compliance scoring
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Different compliance scenarios require different agent combinations and execution sequences; dynamic orchestration ensures appropriate resource allocation.
Core Logic
Coordinates mission execution using Claude Sonnet for sophisticated reasoning. Analyzes mission requirements, assigns appropriate agents, manages execution plans with step-by-step tracking, handles inter-agent messaging, tracks live metrics including tokens, latency, and cost, and ensures mission completion with comprehensive reporting.
Compliance Auditor Agent
CAP checklist requirements span hundreds of items across multiple disciplines; manual review is time-intensive and prone to oversight.
Core Logic
Evaluates laboratory compliance against CAP ANP checklist requirements. Retrieves relevant checklist items through RAG, maps laboratory documentation to requirements, identifies gaps and deficiencies, assesses risk levels for each finding, and generates audit reports with specific remediation recommendations and citation risk assessments.
QC Analyzer Agent
Quality control data requires expert interpretation using Westgard rules and statistical process control; identifying root causes of QC failures demands correlation across multiple variables.
Core Logic
Analyzes QC data using Westgard multi-rule evaluation. Identifies rule violations (1:2s, 1:3s, 2:2s, R:4s, 4:1s, 10x), traces systematic versus random errors, correlates failures with reagent lots, calibrations, and environmental factors, and predicts emerging QC trends before control failures occur.
Data Retriever Agent
Compliance analysis requires data from multiple systems (LIS, QC software, reagent inventory, training records) that must be efficiently retrieved and correlated.
Core Logic
Executes targeted data retrieval across laboratory information systems. Performs vector similarity searches against regulatory document databases, queries specimen databases with complex filtering, retrieves historical QC runs, and correlates data across sources to provide comprehensive context for analysis agents.
Report Generator Agent
Compliance findings must be formatted into actionable reports appropriate for different audiences (lab staff, management, inspectors) with proper citations and evidence.
Core Logic
Generates comprehensive, professionally formatted reports from agent findings. Structures output with executive summaries, detailed findings with confidence scores, specific recommendations with priority rankings, supporting evidence citations, and appendices with raw data. Produces inspection-ready documentation packages.
Risk Predictor Agent
Reactive compliance management addresses issues after they occur; predictive risk assessment enables proactive remediation before violations or patient impact.
Core Logic
Applies predictive models to identify emerging compliance risks. Analyzes trends in QC data, reagent usage patterns, training completion rates, and equipment maintenance records to forecast potential compliance gaps. Generates risk scores with impact assessments and recommends preventive actions prioritized by risk level and remediation effort.
Reagent Tracker Agent
Reagent recalls require rapid identification of all affected specimens and results; manual lot tracing across thousands of cases is time-prohibitive.
Core Logic
Traces reagent lot usage throughout specimen processing history. Identifies all cases processed with specific reagent lots, assesses potential result impact, generates affected patient lists, and produces recall response documentation meeting regulatory notification requirements.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
5 technologies
Architecture Diagram
System flow visualization