INPULSE – A Hive Platform: Solution for Investor Relation: 4-5 Weeks Implementation

The purpose of the solution is to create an efficient knowledge management system for investors and financial relations. By using generative AI, it aims to streamline data extraction from various documents, prioritize relevant content, and provide a user-friendly chat interface for natural language queries hosted on any client-facing public website. This solution improves accessibility to investor information, reduces search time, and enhances the user experience by delivering comprehensive answers with relevant citations and multimedia enrichment.

The system comprises two key components:

1. Data Extraction: This component will extract data from various sources, processing files like PDFs, images, and audio and video content from a centralized repository. The processor will prioritize information by publication date, remove duplicates, and apply optical character recognition (OCR) for images. Video and audio files will be transcribed using services like AI services. A vector database will be created for efficient storage and retrieval of the processed data.
2. Chat Interface: A user-friendly interface will allow users to query the vector database using natural language. It will offer enriched responses in different formats like text, tabular, graphs, images and maintain chat history to provide context for follow-up questions. The system will generate informative answers, include relevant citations, and offer users feedback options.

The project uses the Azure cloud platform and aims to improve access to investor and financial information, enhance user experience, and reduce search time. The system will make it easier for users to find specific data, increasing knowledge retention with direct links to relevant sources.

Base Features:

1. Data Extraction: Data is extracted from a common source, specifically Azure Blob Storage.
2. Supported File Formats: Audio, Video, Images, Text
3. Responsive Web App: The chatbot is accessible on websites and mobile apps through a responsive web app design.
4. Chat Interface: a. Multi-Format Response Handling: The chatbot can respond in various formats, including text, tables, graphs, and multimedia (e.g., video and audio links), ensuring flexible access to information. b. User Feedback Collection: i. A smiley-based rating system allows users to provide feedback at the end of each interaction. ii. Users can also leave additional comments along with their rating. iii. All feedback is securely stored for future analysis. c. Polite Acknowledgment for Unanswered Queries: When the chatbot cannot answer a query, it provides a polite response and suggests alternatives, such as contact details for the helpdesk. d. Textual and Structured Responses: The chatbot can deliver both plain text and structured responses, such as tables and graphs, to provide clear and organized information. e. Contextual Responses: The chatbot maintains context across multiple interactions within a session to ensure coherent and relevant follow-up responses.
5. English Language Support: The application supports interactions in English.
6. Deployment & Configuration: The solution will be deployed and configured in the customer's Azure environment.
7. Timeline: The implementation includes 4 to5 weeks of configuration in one of customer Environment

Advanced Features:

1. Includes All Base Features
2. Multiple Data Source Integration: i. Website scraping ii. Database integration iii. API-based integration
3. Personalized Responses: Tailored responses based on individual user profiles and preferences.
4. User Notifications: Users can subscribe to receive notifications for relevant content and updates.
5. Performance Monitoring: Dashboards for real-time performance tracking, including chatbot performance, user engagement, and feedback analysis.
6. Production deployment and additional Post Go-live support
7. Performance & Security Testing: Thorough testing to ensure optimal performance and security.
8. Multilingual support
9. Timeline for Advanced Features: The timeline will be discussed and determined based on the required advanced feature implementations.

*** Disclaimer: The provided price and timeline apply to the Base Features only