How XR.Voyage overcame scalability and data management challenges with falkordb

XR.Voyage is a cloud-hosted immersive experience platform that aims to gamify exploration, interaction and transformation of your data sets. They operate at intersection of hyperscalers, on-the-fly generated immersive data workstations and knowledge graphs.

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“As one of earliest adopters of FalkorDB (since early 2019), we chose to base our foundation on best-suited technology core but equally to be surrounded by the support team that is an absolute pleasure to work with.” 
Peter Styk profile picture
Peter Styk
CEO

TL;DR

XR.Voyage, a cloud-hosted immersive experience platform, leveraged FalkorDB to overcome scalability and data management challenges.

Technologies & Integrations

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The Challenge

XR.Voyage operates at the intersection of hyperscalers, on-the-fly generated immersive data workstations, and knowledge graphs. Their gamification strategy relies on LangChain agents to connect and exchange information with numerous data providers. However, this complexity posed significant scalability and data management challenges:

  • Efficiently managing 100+ LangChain agents and 1400+ data providers
  • Maintaining isolated back executions per client while sharing front-end modules
  • Ensuring SOC 2 compliance and secure self-maintenance of graph instances
  • Versioning and cross-referencing code bases, classes, and functions

The Solution

XR.Voyage chose FalkorDB as their foundation technology core due to its ability to handle complex graph structures and provide low latency and high accuracy. Key solutions implemented include:

  • Utilizing FalkorDB to manage and cross-reference code self-improvement graphs, versioning of code bases, classes, and functions
  • Implementing isolated back executions per client using FalkorDB Cloud
  • Leveraging FalkorDB’s graph node-relationship structures to attach ownership and objective information to code changes
  • Integrating with multiple LLM providers (OpenAI, Groq, Anthropic, VertexAI, Azure, and Ollama) for hot-swapping models

“Our clients usually aim for document stores of processed/transformed datasets and those used in Virtual Reality Simulations. However, versioning of all codes required to assemble a simulation relies on FalkorDB for reference of versions that passed tests. And that can happen even several hundred times per single VR world.”

The Results

By leveraging FalkorDB, XR.Voyage achieved:

  • Efficient management of 100+ LangChain agents and 1400+ data providers
  • Isolated back executions per client while sharing front-end modules
  • SOC 2 compliance and secure self-maintenance of graph instances
  • Accurate versioning and cross-referencing of code bases, classes, and functions
  • Low latency and high accuracy in their immersive experience platform