GraphRAG & Explainable AI: Building Trustworthy LLM Outputs
Most LLM failures in the enterprise are trust failures: answers lack proof, break compliance, or drift with stale data. GraphRAG adds a knowledge graph layer (Neo4j) to RAG so answers come with traceable evidence paths—linking entities –> source docs –> final response. Microsoft open-sourced GraphRAG and describes its structured, hierarchical retrieval; Neo4j documents how the pattern improves explainability.
Why now
- AI adoption slowed by lack of trust & explainability
- Regulations (EU AI Act, NIST AI RMF) demand transparency & provenance
- Enterprises need evidence-based AI outputs
What GraphRAG is
- Combines knowledge graphs (Neo4j) + retrieval
- Returns answers with citations + graph evidence paths
- Moves beyond plain vector search → context with relationships
Where it applies
- Insurance: claims approvals & denials
- Healthcare: patient summaries with compliance
- Finance: audit trails, risk explanations
- Policy & legal: regulatory interpretations
Why it’s valuable
- Builds trust with executives & regulators
- Improves faithfulness & groundedness of LLMs
- Reduces disputes, errors, and compliance risks
Key takeaways
- GraphRAG design blueprint (schema + ingestion + retriever)
- Evaluation metrics (faithfulness, groundedness, coverage)
- Practical demo patterns (e.g., “Why was this claim denied?”)
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.