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What is Symbolica?

Existing machine learning models are expensive to develop, complex to deploy, difficult to validate, and often produce misleading outputs. At Symbolica, we are fundamentally rethinking the machine learning paradigm. By utilizing the powerful framework of category theory, we design models capable of understanding and learning algebraic structures. This innovative strategy enables our models to possess a thorough and systematic worldview that is both explainable and subject to verification. We aim to empower both developers and end users to understand and communicate the rationale behind model outputs. Achieving this level of interpretability and control—such as the flexibility to exclude proprietary information from training datasets—is vital for applications that are crucial to achieving mission objectives. Furthermore, we are confident that improving transparency in the decision-making processes of models will enhance trust and collaboration between human users and artificial intelligence systems, ultimately leading to more effective partnerships. This commitment to clarity not only benefits users but also strengthens the overall integrity of machine learning applications.

What is FalkorDB?

FalkorDB stands out as a remarkably fast, multi-tenant graph database specifically optimized for GraphRAG, delivering precise and relevant AI/ML results while effectively reducing hallucinations and enhancing overall efficiency. Utilizing sparse matrix representations in conjunction with linear algebra, it skillfully manages complex, interconnected datasets in real-time, which not only lowers the incidence of hallucinations but also improves the accuracy of responses generated by large language models. This database supports the OpenCypher query language, augmented by unique features that promote both expressive and efficient querying of graph data. Moreover, it includes integrated vector indexing and full-text search capabilities, enabling detailed search functions and similarity evaluations within a cohesive database environment. FalkorDB's architecture allows for multiple graphs to coexist within a single instance, thereby increasing security and performance for various tenants. Additionally, it ensures high availability through live replication, making certain that data remains consistently accessible, even during peak demand periods. This array of capabilities positions FalkorDB as an effective solution for organizations aiming to handle intricate graph data efficiently and reliably, making it an essential tool for data-driven decision-making.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
ChatGPT
Cognee
DSPy
Docker
Gemini
Gemini Enterprise
Google Cloud Platform
LangChain
Llama
Mem0
Microsoft Azure
Netlify
OpenAI
Vercel

Integrations Supported

Amazon Web Services (AWS)
ChatGPT
Cognee
DSPy
Docker
Gemini
Gemini Enterprise
Google Cloud Platform
LangChain
Llama
Mem0
Microsoft Azure
Netlify
OpenAI
Vercel

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Symbolica

Company Website

www.symbolica.ai

Company Facts

Organization Name

FalkorDB

Date Founded

2023

Company Location

Israel

Company Website

www.falkordb.com

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

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