The Problem
Problems Faced
Users would likely need to navigate through multiple menus, dashboards, or reports to find the desired information (accuracy, processing time, document count). This process would be inefficient and time-consuming, especially for users dealing with large volumes of documents.
Users would not have immediate access to critical metrics. They would have to wait for reports to generate or manually compile data, delaying decision-making.
Finding specific information within a traditional interface can be challenging, especially for users unfamiliar with the system.
Traditional interfaces lack the conversational ease of a chat interface. This means that users must learn the specific lanuage of the UI, rather than using natural language.
Iterations
Initial Phases of Design
Prioritized Rapid Deployment: The initial design focused on a card-based system to expedite product launch and deliver core functionality quickly.
A deterministic, card-driven interface was implemented to ensure a consistent and predictable user experience, minimizing potential user confusion.
The design embraced a phased development strategy, prioritizing immediate functionality while planning for future NLP integration.
Avoiding NLP in the initial phase reduced the risk of user confusion, ensuring clarity and ease of use.
Final Design
Features
Natural Language Processing Integration: Staple Chat now features NLP, allowing users to interact through conversational queries, enhancing ease of use.
Intuitive Chat Input Area: A clearly defined "Message Staple Chat" area provides a straightforward space for users to type their questions.
Multiple Query Options: The design offers both NLP and quick action buttons, catering to diverse user preferences.
Evolution from Card-Based System: The shift to NLP represents an iterative improvement, enhancing functionality based on user needs.
Final Design
Flow:
Due to backend limitations that hindered real-time graph rendering within the UI, a pragmatic solution was implemented. Users can now download query results as CSV files.
To enhance user efficiency and streamline workflows, a "Save Query" feature was introduced. This allows users to store frequently used or complex queries, eliminating the need to re-enter them.
The Impact
Concluding the Chat Feature
The chat interface, especially with NLP, allows for faster retrieval of document metrics compared to traditional navigation. Users can quickly access information without navigating complex menus.
The intuitive chat interface, combined with quick action buttons, provides a more user-friendly and engaging experience compared to traditional interfaces.
Instant access to key metrics empowers users to make informed decisions quickly, improving overall productivity.
Future Enhancements
Future Scope
A key future enhancement will be the implementation of real-time graph rendering within the Staple Chat interface. This will eliminate the need for CSV downloads and provide users with immediate visual insights into their document metrics, enhancing data comprehension and analysis.
The long-term vision for Staple Chat is to enable users to interact with all documents within the platform through conversational queries. This will allow for comprehensive document analysis and the extraction of valuable insights across the entire document repository, transforming Staple AI into a powerful knowledge discovery tool.
