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Start your journey from data to knowledge

With Datavid's knowledge graph implementation, your organization can extract the most value from its data.

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Helping world-class companies with knowledge graph implementation

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Your business likely generates vast amounts of data, so if you find it difficult to see and understand the big picture, you're not alone.​

​Most of our customers feel the same pressure:​

"How do I make the most of all this data?"​

​Datavid offers an answer by developing and maintaining knowledge graphs that tell the full story of your enterprise, taking you on a journey from a data-driven to a knowledge-driven mindset (i.e. real-world business value).​

You will be able to store, manage, query, and extract insights from any dataset using a graph-like structure and visualize it seamlessly across applications.​

Unify data silos and extract metadata

Disparate data sources don't give you the full picture.

Datavid helps you create knowledge graphs which provide a comprehensive view of your domain.

Visualize the flow of information

Knowledge graphs provide a great visual network of information. You can then display this flow as it relates to relevant business processes.

Comply with data regulations

Datavid helps you trace data lineage, protect personal information, and run custom reports—all through the power of knowledge graphs.

Make knowledge graphs your company's superpower

A well-implemented knowledge graph can turn the tides from expensive research programs that require days of manual labor just to derive one insight to almost instant business context delivery.

OUR WORK IN YOUR INDUSTRY
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Pull your company's knowledge together

With a knowledge graph, your company's stakeholders get to see the full picture. Datavid will help you achieve a 360-degree view of business and how it relates to the real world around you. By seeing the connections (instead of guessing them), it becomes easier to make the right decisions.

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Unlock entirely new company insights

By structuring data in context to the real world, Datavid's knowledge graph implementation brings entirely new insights to the forefront. Instead of focusing on the graph technology itself, your organization will benefit from business-driven development—delivering value upfront.

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Answer complex business questions

Get contextual responses to your business queries with knowledge graphs that can easily filter through the noise and get to the core of your problem. The result is more focused software that answers your organization's questions directly—no filler or endless lists of documents to review.

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CASE STUDY

Extracting knowledge from decades of data

With almost 50 thousand team members spread across the globe, Syngenta is a powerhouse in farming and agrochemicals—a dominant leader in many of its applications worldwide.

Syngenta came to Datavid with a huge challenge to solve: indexing more than 16 million files spread across dozens of data sources which contained decades worth of siloed knowledge.

Datavid developed a semantic data platform for Syngenta, with the capability to index and retrieve specific agrochemical concepts extracted from "foam tree" ontologies.

The result was a drastic reduction in research time from several weeks to just a few hours, enabling research across a vast body of knowledge previously unavailable to the R&D team.

Read the full case study →

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Datavid is helping Syngenta's scientists identify concepts that are relevant to their research more quickly, ultimately saving time and effort on a weekly basis.

Graham Mullier

HEAD OF CONTENT DIGITISATION, SYNGENTA

Your questions. Answered.

One of the most popular knowledge graphs is the "Google Knowledge Graph." However, the popularity and relevance of knowledge graphs can change over time.

Yes, knowledge graphs are often used as a component of Natural Language Processing (NLP) systems to enhance their understanding of language by incorporating structured knowledge and relationships between entities.

Knowledge graphs are often used in AI systems, but they are not the entirety of AI. AI is a broad field encompassing various techniques and technologies, including machine learning, neural networks, natural language processing, robotics, and more. Knowledge graphs are a tool or resource used within AI to represent structured knowledge and enhance AI's understanding and reasoning capabilities.

Take your organization's data practices to new heights

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