Semantic Knowledge for Artificial Intelligence
The Progress® Semaphore™ semantic platform helps you leverage your data for generative AI, fueling explainable, relevant and trustworthy outcomes.
Data in Context Drives AI Initiatives
Artificial Intelligence (AI), particularly generative AI and machine learning, has become a priority for businesses due to its ability to interpret data and enable smarter operations by leveraging large language models (LLMs) in critical applications and systems. However, these data-human interactions need to be regularly monitored to reduce hallucinations and data biases and facilitate more accurate output. Merging generative AI with semantic technologies and knowledge graphs can deliver value to digital ecosystems by applying human insight and context to data at a machine scale.
Conversational Agents
Document Q&A Systems
Semantic Enterprise Search
Content Generation
Semantic Retrieval Augmented Generation
The effectiveness of generative AI depends on the data it uses to generate results. Semantic Retrieval Augmented Generation (RAG) allows users to augment prompts by incorporating enterprise data, guiding the model to generate contextually relevant responses and reducing hallucinations and data biases for more precise AI outputs. Prepopulating generative AI's short-term memory with semantically relevant enterprise knowledge can enhance the results of AI systems, providing context, meaning and insight into the data used by AI.
Business Benefits of RAG:
- Achieves consistent results, facilitating trust in the generative AI
- Improves accuracy, with unbiased data results and fewer hallucinations
- Enhances results with the ability to change out generative AI models quickly and inexpensively
- Enables human understanding, auditability and operational insights
- Supports intuitive prompt creation and response understanding
Technical Benefits of RAG:
- Feeds in semantically relevant enterprise data
- Supports natural language feeding of the generative AI’s prompt, making it human readable
- Functions independently of the generative AI model being used
- Has tunable, use-case dependent relevancy
- Adheres to enterprise standards for governance, lineage and provenance
Webinar
Building knowledge models can be a daunting task. Combining generative AI with a human in the loop, using the powerful Semaphore technology, can make you more productive in the creation, enrichment and management of your semantic models.
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How Semaphore Supports Your Business
Progress Semaphore is a semantic platform that supports knowledge-centric architectures, enabling companies to use enterprise knowledge more effectively through data quality enhancement, data enrichment, data governance and knowledge management practices. These are critical for enabling AI models to deliver quality results.
Knowledge Governance
Semaphore is moderated and instructed by business users. SMEs are responsible for the management, development and maintenance of knowledge models over their lifetime. The models represent relevant knowledge in the language and vocabulary used by the business to provide qualified contextual data.
Data
Quality
Semantic metadata—data that is harmonized, enriched and extracted—provides a holistic view of all enterprise information, structured and unstructured, internal and external to the organization. It improves data quality, reduces noise and results in a higher precision of prediction, which is important since the quality of information affects outcomes.
Auditable Outcomes
Semaphore provides a transparent approach for harmonizing information differences. As the semantic platform evaluates the information and makes decisions, the knowledge model and metadata provide a clear and explicit picture of the information used and actions taken in the decision-making process.
Repeatable Outcomes
Semaphore provides precise, complete and consistent results. By leveraging a knowledge model and rule-based classification and fact extraction, information is processed consistently and decisions and outcomes are repeatable, transparent and fact-based.
Webinar
Modern enterprises are data-driven, and generative AI technologies need secure access to that enterprise data in a form that is sufficiently rich, real-time and accurate to deliver more trustworthy and quality results. Combine the semantic capabilities of Semaphore with the Progress® MarkLogic® platform for greater insights and more accurate, trustworthy answers.
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Trustworthy AI with Semaphore
Semaphore can help you realize the potential of your data and get high-quality and trustworthy generative AI results. Get in touch to learn how we can help support your data needs.