ThunderGraph is advancing model based systems engineering (MBSE) for complex automotive systems by transforming technical documentation into structured knowledge graphs. The platform creates digital sources of truth that automatically generate system architectures, requirements hierarchies, and component relationships using SysML driven workflows. Built on AWS ECS with a Next.js frontend, FastAPI backend, Neo4j graph database, and Redis workers, ThunderGraph processes engineering documents to create traceable links between documentation and system elements.
Problem: traditional compliance software slows document traceability
Automotive engineering teams manage large volumes of requirements, specifications, and compliance documents across multiple versions. Traditional compliance management software relied on manual tracking, spreadsheet based traceability, and static review workflows, which slowed engineering processes and increased compliance risks.
ThunderGraph identified key challenges including difficult citation mapping, time consuming document reviews, unreliable position based comparisons, and limited visibility into downstream impact when requirements changed. These gaps reduced traceability accuracy and increased compliance review effort.
Solution: AI powered document traceability for compliance
GoML built an AI powered compliance management software platform using graph databases, vector search, and LLMs to automate traceability and compliance review. The solution leveraged GoML’s Agentic AI Accelerator for workflow orchestration capabilities for citation reasoning and impact analysis.
AI powered document version management
ThunderGraph automatically detects, tracks, and manages document versions within the same document family.
Key improvements:
- Automatic version detection and tracking
- Duplicate content detection using SHA-256 hashing
- Metadata extraction and validation
- Version lineage and supersession tracking
- Automated processing status management
AI citation generation and traceability intelligence
The compliance management software automatically creates and updates citations between engineering elements and source documents.
Key capabilities:
- Semantic vector search for relevant content
- AI based citation relevance scoring
- Automatic citation regeneration
- Confidence based traceability validation
- Historical citation preservation for audits
- Hybrid graph and vector search workflows
AI powered impact analysis
ThunderGraph uses AI driven impact analysis to classify the effect of document changes across downstream system models.
Key capabilities:
- Identifies affected engineering elements
- Compares old and new traceability mappings
- Classifies impact severity automatically
- Flags high risk changes for review
Impact classifications:
- Unchanged
- Minor Edit
- Significant Change
- Not Found
Compliance review workflow and audit automation
The platform includes structured review and approval workflows for compliance management.
Key capabilities:
- Accept or update citations
- Escalate high risk changes
- Track reviewer identity and timestamps
- Maintain complete audit history
- Store review notes and escalation reasons
Compliance dashboard and reporting
ThunderGraph provides audit ready reporting for enterprise compliance workflows.
Available reports:
- Requirements Traceability Matrix
- Document Version Register
- Citation History
- Review Audit Trail
Interactive user experience
The platform streamlines compliance workflows with:
- Automatic citation regeneration
- Real time notifications
- Centralized compliance dashboard
- Review status visibility
- Structured audit history retrieval
Infrastructure and deployment
The platform uses a scalable cloud architecture built with:
- FastAPI
- Neo4j
- AWS Bedrock
- Redis
- AWS S3 and MinIO
- ARQ workers
- AWS Cognito
- Cohere Embed v4
Quality assurance
Validation focused on:
- Document version accuracy
- Citation regeneration validation
- Semantic similarity testing
- Impact classification accuracy
- Audit trail verification
- Workflow escalation testing
- Role based access validation
Impacts
- 40% faster compliance review workflows
- 60% reduction in manual citation management effort
- 35% improvement in traceability accuracy across document revisions
- 50% faster audit readiness for ISO 26262 and ASPICE compliance programs
About
Before Gen AI and after Gen AI
“With AI powered compliance management software, ThunderGraph transformed document traceability into an intelligent, audit ready workflow that improves engineering compliance accuracy and operational efficiency.”
Prashanna Rao, Head of Engineering, GoML
Key takeaways for enterprise compliance management software
Common challenges
- Manual traceability workflows do not scale
- Document version changes create downstream compliance risks
- Static comparison systems fail for complex engineering documents
- Audit preparation requires excessive manual effort
Practical guidance
- Use AI powered compliance management software for automated traceability
- Combine graph databases and vector search for semantic document mapping
- Automate citation regeneration during document updates
- Implement confidence based review escalation for high risk changes
- Maintain complete audit trails across compliance workflows
Ready to build AI powered compliance management software solutions
Partner with GoML to build scalable AI powered compliance management software systems using Gen AI and AI Matic.
