Content tagging solution for CMS powered by AI

Solution

Our approach to the project began with a structured series of planning and discovery sessions aimed at comprehensive understanding of the intricacies of content tagging requirements. The team focused on key aspects such as accepting and rejecting proposed tags, introducing new tags, and managing the taxonomy tree.

Once discovery phase has been completed, AI architect designed a solution that includes the following features:

• AI-driven tag suggestions: utilizes advanced LLMs to automatically generate relevant and accurate tag suggestions based on the content.
• Optimized tagging process: significantly reduces the time content authors spend on manual tagging, allowing them to focus on content creation.
• Custom tag management: enables authors to accept or reject proposed tags and introduce new tags, ensuring flexibility and control over content categorization.
• Taxonomy tree management: provides a structured approach to managing tags, enhancing the organization and retrieval of content.
• Guardrails for tagging: implements measures to prevent the use of misleading or irrelevant tags, maintaining the integrity of the tagging system.