GenAI Augmented Structured Content

Digital Transformation with
GenAI Augmented Structured Content

Maximizing GenAI Efficiency through Structured Content
Improving GenAI Outputs with Prompt Specificity
The Role of Structured Content in Improving Prompt Specificity
The InteliNotion Solution: GenAI-Assisted Structured Authoring

The following diagram illustrates the InteliNotion solution flow for
GenAI-assisted Structured Content Authoring:

Component Prompt Configurations

GenAI-Assisted Authoring

View and edit prompts as needed.
Save revised prompts as new versions.
Pose questions related to document or component content, to further refine previously AI-generated content.
The following are some examples of component-based GenAI use cases:
Writing a clinical protocol Study Design component using publicly available information or proprietary information from previously written protocols.
Writing a 2-paragraph summary of data contained in an in-text demographics table in a clinical study report results section.
Writing a protocol synopsis component by summarizing the content in one or more source components from the body of the protocol.
Summarizing the content from one or more protocol components into a methodology/front end component of a clinical study report, if the content is not suitable for as is reuse from protocol to clinical study report.
Changing from present to past tense of any component reused from the protocol into a clinical study report methodology section.
Enhancing AI Capabilities through LLM and RAG
Model Flexibility and Adaptability
Adaptive LLM updates and reconfiguration through API based integration
Advanced RAG modeling for efficient content structuring and training
Flexible APIs for tailored integration with our customers’ own models and knowledge sources