Accelerate Insights
Reduce the time and effort required to build knowledge graphs substantially, enabling faster discovery and decision-making.
BioChatter
Revolutionizing Knowledge Graphs and Conversational AI in Biomedicine
Unlock the potential of your biomedical data with BioCypher and BioChatter, two cutting-edge, open-source frameworks designed to transform how researchers manage, integrate, and utilize data. The Hyve specializes in deploying, customizing, and supporting these frameworks to meet the unique needs of your research or business.
Why Choose BioCypher & BioChatter?
Enhanced Collaboration
Harmonize data sources with consistent ontologies and streamlined processes.
Intuitive Exploration
Talk to your data and get new insights to enhance your research.
Community-Driven Innovation
Open-source tools that foster collaboration and innovation in the biomedical community.
Key Features
BioCypher: The Unified Knowledge Graph Framework
Modular Data Integration: Seamlessly integrates diverse data sources into the framework using customizable ETL processes.
Ontology Mapping: Link and merge ontologies to create consistent semantic foundations for your knowledge graph.
Flexible Outputs: Export data in formats like Neo4j, SQL, or RDF to match your use case.
- Reproducible Workflows: Utilize low-code configurations to ensure workflows are reproducible and easily shareable.
BioChatter: Bridging Knowledge Graphs and Conversational AI
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Generative AI Integration: Connect knowledge graphs to large language models for advanced querying and insights.
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RAG Implementation: Use retrieval-augmented-generation to upload your own documents and get the information you’re looking for.
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Custom Frameworks: Agile and robust backend systems tailored for biomedical applications.
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Streamlined Interfaces: Choose a user-friendly interface or integrate it seamlessly into your custom front-end.
- Future-Ready: Expandable to support AI-driven insights, causal reasoning, and emerging technologies.
Services we offer
Consultancy
Comprehensive business analysis to define requirements and strategies for a successful Graph AI implementation.
Semantic Data Modeling
Design and implement semantic frameworks tailored to your specific use cases, ensuring robust and interoperable knowledge graph structures.
Pilot Projects
Start small with a focused pilot to validate Graph AI capabilities and demonstrate value before scaling up.
Full-Scale Implementation
Transition seamlessly to a full-fledged implementation, integrating public and internal data through custom adapters and ontological mappings.
User-Training
Equip your team with hands-on training for effective use and maintenance of Graph AI frameworks.
Ongoing Support
Stay ahead with continuous updates, technical support, and contributions to the open-source community.
Why is a Knowledge Graph important?
Having all data in a structured, queryable model speeds up research and development processes, enables maximum (re)use of the data and stimulates internal and external collaboration.
With knowledge graph capability, data integration is simplified because the meaning has been standardized. Processes can be automated, reducing the need for reconciliation. Data teams get analytical flexibility and the ability to ask ‘what if’ questions to the data. Data stewards can manage data more efficiently as all data points as well as the relationships between data elements are captured.
Book a session with our experts
Discover how these open-source tools, combined with The Hyve’s expertise, can revolutionize your data strategies. Explore a hands-on demonstration of BioCypher and BioChatter in Open Targets to understand their capabilities. Visit the Open Targets demo server.
BioCypher and BioChatter are not limited to Open Targets—they’re designed for diverse data use cases. Let’s start the conversation to explore how they can work for your specific needs!