Knowledge base and FAQ creation is a very time-consuming activity. Zinger can automatically create Q&A pairs from long-format documents, videos, and websites. To help users get to the exact answer from deep within documents we’ve built the following toolsets.
- Q&A generation
- KI-NLP for exact answers
Training a chatbot to complete tasks is simple compared to determining a set of tasks to configure. Creating a long list of tasks that the bot can perform, and then configuring the forms, flows, and functions to go with it is very time-consuming. Besides, without a menu, it is challenging for the users to know which tasks can be achieved conversationally.
Zinger has developed the following capabilities to build an exhaustive list of tasks from relevant documents to create a universe of tasks.
- Task extraction from Guides/Menus
- Intent and Entity from API documentation
- Link extractor that extracts system, screen, and helpdesk links from documents
Users have to get data and insights from multiple systems. Zinger’s Data and Insight query module is able to use multiple approaches below to service data requests.
- API-based Data Query
- Data Graphs
- ML-based model outputs
Auto-generates FAQ database by parsing documents and videos.
Auto-identifies tasks from user guides and help manuals.
Auto-creates Intent and Entities from API documentation.
Delivers superior NLU performance compared to popular NLU Engines.
Uses Large Language Models,
Pre-Trained Models, and Generative AI to reduce training samples and training iterations
Creates dynamic guided bot flows from user guides and training manuals, automatically.
Auto-creates forms from API documentation.
Uses AI to generate qualifying questions and route to helpdesk.
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