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Top Knowledge Graph Companies

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40 companies for Knowledge Graph

Data Language's Logo

Data Language

Mole Valley, United Kingdom

A

11-50 Employees

2014

Key takeaway

The company specializes in the design, implementation, and deployment of knowledge graphs (KGs), offering a Knowledge Graph as a Service platform that enhances exploration and accelerates time-to-market. Their expertise in scalable data engineering and digital media KGs, rooted in experience from the BBC, positions them as a leader in this field.

Highlighted product

Product

Knowledge Graphs

Data Language is a market leader in the design, implementation, and deployment of knowledge graphs (KGs), and we have developed a Knowledge Graph as a Service platform that enables exploration and speed-to-market.

BioBox Analytics's Logo

BioBox Analytics

Old Toronto, Canada

A

1-10 Employees

2019

Key takeaway

The company's mission is to unify biological knowledge into a searchable resource, enabling scientists to extract meaningful insights and identify complex patterns within multi-modal data. Their BioBox Knowledge Engine facilitates data-driven decisions in drug and disease research, highlighting the importance of Knowledge Graph Search in organizing and accessing critical information efficiently.

Highlighted product

Product

Knowledge Graph Search

DataBorg's Logo

DataBorg

Hamburg, Germany

A

1-10 Employees

2020

Key takeaway

DataBorg offers a comprehensive knowledge management suite that enables businesses to effectively utilize their data through intelligent solutions, including a Text To Knowledge Graph API. This platform integrates distributed knowledge into a cohesive repository, facilitating enhanced data understanding and insights, which are crucial for applications in AI and Business Intelligence.

Highlighted product

Product

DataBorg - Text To Knowledge Graph API

DataBorg provides an all-in-one AI-powered platform for consumers and businesses that allows them to improve data understanding through knowledge extraction, integration and analysis.

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FactNexus's Logo

FactNexus

Newcastle, Australia

A

1-10 Employees

2010

Key takeaway

The company offers a range of Knowledge Graph services, including support for other large language models (LLMs) and tools that enable domain experts to contribute to structured knowledge. Their innovative product, beth.ai, is a Generative Knowledge Graph AI designed to simplify the creation and management of knowledge graphs.

Highlighted product

Core business

factnexus | knowledge empowered

Metreeca's Logo

Metreeca

Milan, Italy

B

1-10 Employees

-

Key takeaway

Metreeca utilizes knowledge graphs to address real-world data challenges, leveraging linked data and advanced technologies like natural language processing and machine learning to create agile data solutions. This approach helps to organize and make use of fragmented and unstructured data effectively.

Highlighted product

Product

Solutions | Metreeca

Data Lens Ltd's Logo

Data Lens Ltd

London, United Kingdom

A

11-50 Employees

2019

Key takeaway

The company specializes in building enterprise knowledge graphs quickly and efficiently, offering tools that automate graph data production and facilitate easy migration between graph database vendors. With over a decade of experience, they provide comprehensive knowledge graph solutions and consulting services to support organizations at all stages of adoption.

Highlighted product

Service

Knowledge Graph and Graph Database Consulting Services

The team have been working in the knowledge graph space for over 10 years providing services to companies whatever their stage of knowledge graph adoption.

StreamScape's Logo

StreamScape

New York, United States

B

11-50 Employees

2011

Key takeaway

StreamScape offers a tailored environment for rapid application development, highlighting their expertise in advanced data visualization tools, including knowledge graphs, which can significantly enhance data management and accessibility.

Highlighted product

Product

StreamScape | Knowledge Graphs

Yext's Logo

Yext

New York, United States

B

1001-5000 Employees

2006

Key takeaway

The Yext Answers Platform leverages a Knowledge Graph, which is a structured database of real-world entities and their relationships, to help brands effectively capture and retain consumer traffic from across the web.

Highlighted product

Product

Knowledge Graph | Yext

Yext experiences are built on a Knowledge Graph, your own brain-like database that is structured with real-world entities and their relationships.

agnos.ai's Logo

agnos.ai

London, United Kingdom

A

11-50 Employees

2018

Key takeaway

Agnos.ai specializes in enterprise knowledge graphs (EKGs), offering platforms that connect data silos and enhance business applications through semantic technology and open standards. Their team includes experienced knowledge graph architects and engineers, emphasizing a unique approach to data challenges in complex environments.

Highlighted product

Core business

Semantic and Enterprise Knowledge Graph Solutions — agnos.ai

We at agnos.ai are Knowledge and Semantic Graph consultants looking for access to EKG-related best practices open standards to help our clients navigate data across the enterprise. Learn more!

Graphifi's Logo

Graphifi

Norwich, United Kingdom

A

1-10 Employees

2019

Key takeaway

Graphifi Ltd offers services and products specifically designed for building Knowledge Graphs, including taxonomy and ontology management, as well as professional services to support your data journey.

Highlighted product

Core business

Graphifi

Services and products for building Knowledge Graphs. Taxonomy and ontology management. Knowledge graph platforms. Professional services.


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Things to know about Knowledge Graph

What is a Knowledge Graph?

A Knowledge Graph serves as a structured representation of knowledge that captures relationships between entities, concepts, and facts. It organizes information into nodes and edges, where nodes represent entities like people, places, or organizations, and edges illustrate the connections or relationships among them. This framework enables machines to understand context and semantics, facilitating better information retrieval and enhancing user experience across various applications. Utilized by major tech companies, Knowledge Graphs improve search engine results by delivering relevant information directly to users. They also play a crucial role in applications such as virtual assistants and recommendation systems, allowing for more accurate and context-aware interactions.


How does a Knowledge Graph work?

A Knowledge Graph operates by structuring and organizing information in a way that enhances understanding and retrieval. It uses a network of interconnected entities, such as people, places, and concepts, along with their attributes and relationships to one another. By linking data points, it allows for a more contextual search experience, enabling systems to answer complex queries with relevant information. When a user searches for a specific term, the Knowledge Graph identifies related entities and provides a comprehensive overview by displaying connections and context. This not only improves the accuracy of search results but also enhances user experience by delivering information in a more intuitive manner. As a result, Knowledge Graphs are essential tools for search engines and applications that aim to provide users with meaningful insights quickly.


What are the benefits of using a Knowledge Graph?

1. Enhanced Search Results
Utilizing a Knowledge Graph can significantly improve search results by providing structured data that enhances the relevance of information presented to users. This leads to more accurate and contextually rich search experiences.

2. Better Understanding of Relationships
A Knowledge Graph captures the relationships between entities, allowing for a deeper understanding of how various data points interconnect. This interconnectedness can help users find relevant information faster and aids in data analysis.

3. Improved User Engagement
By delivering concise and relevant information quickly, Knowledge Graphs can increase user engagement. Users are more likely to interact with content that is easily accessible and informative, fostering a better overall experience.

4. Support for AI and Machine Learning
Knowledge Graphs serve as a foundational element for AI applications, helping algorithms to understand context and semantics. This support can lead to more intelligent responses and interactions in various applications.


How can a Knowledge Graph improve data management?

A Knowledge Graph enhances data management by creating a structured representation of information that allows for better organization and retrieval. By integrating diverse data sources, it establishes relationships between entities, making it easier to understand context and relevance. Additionally, this structured approach facilitates data interoperability, enabling various systems to share and utilize information seamlessly. Consequently, users can access insights faster and with greater accuracy, significantly improving decision-making processes and operational efficiency.


What technologies are used to build a Knowledge Graph?

A Knowledge Graph is built using a variety of technologies that facilitate data integration, semantic representation, and querying. At its core, graph databases like Neo4j and Amazon Neptune are employed to store and manage graph data structures, allowing for efficient relationships between entities. Additionally, semantic web technologies such as RDF (Resource Description Framework) and OWL (Web Ontology Language) enable the representation of knowledge in a machine-readable format. These technologies work in conjunction with natural language processing (NLP) tools to extract and understand information from unstructured data sources, ensuring the Knowledge Graph is up-to-date and contextually relevant.


Insights about the Knowledge Graph results above

Some interesting numbers and facts about your company results for Knowledge Graph

Country with most fitting companiesUnited States
Amount of fitting manufacturers4387
Amount of suitable service providers3978
Average amount of employees11-50
Oldest suiting company2006
Youngest suiting company2020

Geographic distribution of results





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Frequently asked questions (FAQ) about Knowledge Graph Companies

Some interesting questions that has been asked about the results you have just received for Knowledge Graph

Based on our calculations related technologies to Knowledge Graph are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce

Start-Ups who are working in Knowledge Graph are DataBorg

The most represented industries which are working in Knowledge Graph are IT, Software and Services, Other, Marketing Services, Education, Research

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Related categories of Knowledge Graph