FalkorDB, Inc.
FalkorDB builds an open-source, low-latency graph database and managed cloud platform for AI agents, GraphRAG and other workloads involving highly connected data. Its mission is to make organizational data actionable, accurate and usable in reliable, scalable AI applications.
At a Glance
- Enterprise AI and software engineering teams
- Data engineers, data scientists and analysts
- Financial services, fintech and compliance teams
- Cybersecurity and identity/access teams
- +3 more
AI Tools by FalkorDB, Inc.
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FalkorDB
Open Source Graph Database for AI
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Latest News
Published 'Why Fraud Checks Catch Honest Customers and Miss Fraud Gangs,' describing fraud and money-laundering agent implementations on FalkorDB.
Announced FalkorDB 6.0, the first release built on the new Rust engine.
Released GraphRAG SDK 1.0, an open-source production knowledge-graph pipeline framework.
Announced FalkorDB on Snowflake as a Native App for graph queries over Snowflake data.
Products & Services
Redis-based, multi-tenant property-graph database with OpenCypher support, sparse-matrix storage and low-latency traversal; deployable locally with Docker or from source.
Fully managed cloud graph and vector database service with free, Startup, Pro and Enterprise plans, multi-graph and multi-tenancy support, and deployment on AWS and GCP; Azure is available for Enterprise BYOC.
Web UI for running queries and visualizing graphs, exposed on port 3000 in the standard Docker deployment.
Open-source toolkit for GraphRAG pipelines, including ontology discovery, knowledge-graph construction, ingestion of structured and unstructured data, entity resolution and multi-agent orchestration.
Market Position
FalkorDB positions itself as a low-latency, Redis-compatible and OpenCypher-compatible alternative for AI-native graph workloads, emphasizing sparse-matrix/linear-algebra execution, multi-tenancy and GraphRAG rather than only general-purpose graph analytics. Its comparison set includes Neo4j, Memgraph, TigerGraph and AWS Neptune, while its graph-plus-vector approach also competes with vector databases and Microsoft GraphRAG-style retrieval stacks.
Leadership
Founders
Guy Korland
CEO and co-founder; former Redis executive and database engineering leader with experience developing high-speed databases and leading development groups.
Roi Lipman
CTO and co-founder; former Redis executive who conceived the idea for the database more than eight years before founding FalkorDB and helped develop its technology.
Avi Avni
Chief Architect and co-founder; former Redis employee and database expert who contributed to C# and F# programming-language development and independently developed a similar database concept before joining his co-founders.
Executive Team
Guy Korland
CEO & Co-Founder
Former Redis executive; database engineering leader with high-speed database experience.
Roi Lipman
CTO & Co-Founder
Former Redis executive and the original conceiver of the FalkorDB database concept.
Board of Directors
Founding Story
The founders started FalkorDB after observing that enterprises could not reliably deploy LLM applications because vector and search systems did not provide sufficient accuracy, traceability or access to internal organizational knowledge. Drawing on their Redis and graph-database experience, they set out to combine a very low-latency graph engine with GraphRAG so LLMs could retrieve connected, current context before generating answers.
Business Model
Revenue Model
Open-source software supports adoption, while FalkorDB Cloud monetizes managed database capacity and production features through tiered subscriptions/resource-based pricing. Enterprise customers can purchase tailored plans and support; the company also distributes through cloud marketplaces and offers commercial integrations.
Pricing Tiers
Multi-graph, multi-tenancy and graph access control; community support.
Adds TLS and automated 12-hour backups; community support.
Adds cluster deployment, high availability, multi-zone deployment, scalability and continuous persistence; business-hours support.
Adds VPC, custom backups, advanced monitoring, enterprise 24/7 support and a dedicated account manager.
Target Markets
- Enterprise AI and software engineering teams
- Data engineers, data scientists and analysts
- Financial services, fintech and compliance teams
- Cybersecurity and identity/access teams
- Supply-chain and operations organizations
- SaaS companies requiring tenant-isolated agent memory
- GraphRAG and enterprise generative AI
- AI-agent memory and agentic workflows
- Fraud detection and anti-money-laundering network analysis
- Cybersecurity and access/permission management
- Supply-chain relationship analysis
- Real-time recommendations
- Walmart
- HSBC
- BMW
- Maersk