With Data Moderator, enterprise content undergoes thorough scanning to identify errors, contradictions, or outdated information.
The significant promise lies in granting conversational access to valuable enterprise knowledge. However, for many enterprises, their data is riddled with contradictions, outdated information, and errors. It’s often incomplete, inconsistent, or contains inaccuracies.
LLaMB’s Data Moderator AI actively monitors enterprise content for errors and inaccuracies and offers guidance on areas that require updating, correction, or even elimination. Data Moderator enables enterprises to improve data management, priming it for use as training data to achieve optimal results with models.
LLaMB Knowledge Graph
LLaMB provides visibility into ingested content through a knowledge graph, displaying relationships across key entities. It generates content-specific dictionaries and extracts abbreviations and taxonomies for developer review, validation, and updates.
LLaMB Analyze
This tool scans enterprise content to identify weak, contradictory, or outdated information. It offers suggestions and options for users to rectify these issues. Specifically, when dealing with data from sources like support ticket logs or tables with relationships, our tools can pinpoint data inconsistencies for user action.
LLaMB Enrich
Using user interactions and detailed topic analysis, LLaMB suggests areas where content requires updates or identifies specific topics for which new content is necessary.