Get GraphRAG Right with Our SDK
A specialized toolkit for building Graph Retrieval-Augmented Generation (GraphRAG) systems, integrating knowledge graphs, ontology management, and large language models (LLMs) to deliver accurate, efficient, and customizable RAG workflows.
- OPEN-SOURCE
- STRUCTURED & UNSTRUCTURED DATA
- OPTIMIZED FOR AI
Remove the barrier of ontology creation
Transform raw data into structured knowledge models automatically.
- Use generative AI to detect and construct ontologies from your datasets
- Review, modify and iterate on detected ontologies to optimize graph structures
- Define custom parameters to scope and control ontology detection processes
Handle structured and unstructured data
Ingest diverse data formats through a streamlined ETL process
- Process multiple file formats including PDF, CSV, HTML, TXT, JSON and URLs
- Deploy FalkorDB instances via cloud infrastructure or containerized environments
- Utilize genAI capabilities to construct knowledge graphs efficiently
Handle structured and unstructured data
Ingest diverse data formats through a streamlined ETL process
- Process multiple file formats including PDF, CSV, HTML, TXT, JSON and URLs
- Deploy FalkorDB instances via cloud infrastructure or containerized environments
- Utilize genAI capabilities to construct knowledge graphs efficiently
Use multi-agent Orchestration
Coordinate specialized agents for complex knowledge operations
- Configure domain-specific Knowledge Graph agents for targeted analysis
- Implement orchestration layer for automated agent coordination and planning
- Execute sophisticated queries through multi-agent collaboration
Practical Use Case
Regulatory Compliance Analyzer
Stay ahead of financial regulations with GraphRAG-SDK.
- Extract Key Requirements: NLP-driven analysis organizes regulatory mandates into a knowledge graph for precise insights.
- Map Regulations to Processes: Link policies to workflows, ensuring compliance across departments.
- Identify Compliance Gaps: Query relationships to spot misalignments and track updates.
- Suggest Improvements: Get data-driven recommendations to refine policies, training, and risk management.
Practical Use Case
AML Network Analyzer
Detect and analyze financial crime with GraphRAG-SDK.
- Trace Fund Flows: Visualize transaction networks across institutions to track money movement with clarity.
- Identify Shell Companies: Uncover hidden relationships and detect illicit entities within financial ecosystems.
- Flag Suspicious Patterns: Use graph-based analysis to detect anomalies, refine detection over time, and scale AML efforts effectively.
Practical Use Case
Financial Product Recommendation Engine
Deliver precise financial recommendations using GraphRAG-SDK.
- Analyze Customer Data: Structure financial records and life events into knowledge graphs for relevant, personalized insights.
- Map Product Relationships: Clearly visualize connections between products, customer segments, and risk profiles.
- Tailored Recommendations: Leverage graph reasoning to offer transparent, explainable suggestions, boosting trust and satisfaction.
Build fast and accurate GenAI apps with GraphRAG SDK at scale
FalkorDB offers an accurate, multi-tenant RAG solution based on our low-latency, scalable graph database technology. It’s ideal for highly technical teams that handle complex, interconnected data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
