Building a GenAI Powered Self-Serve Analytics solution

Every business wants to leverage the actionable insights that lie hidden in their data.

This need spans organizations, from medium scale companies to giant firms. At Infogain, we encountered a similar situation with our client, a huge software firm. The firm supports 13 key products on sites that include over 10,000 web pages. These sites drive and sustain a significant portion of digital revenue and billions of customers visit them annually, so the marketing, content, and publishing demands for an operation of this size are massive.

The firm wanted to leverage its data to improve this digital presence, but their content operations had significant problems, including:

• Information overload
• Data siloing
• Non-actionable insights
• Lack of data lineage
• No single source to consume insights

Clearly, it needed a modern AI-enabled holistic content ops solution.

To mitigate and resolve these challenges. Our team implemented a GenAI-powered self-serve analytics solution, aimed at addressing these challenges and enhancing the data insights process.

The data leveraged for this solution is unstructured in nature which included:

• Performance data reports from Adobe Analytics, captured across various metrics like visits, conversions, and sign-ups.
• Existing dashboards, reports, and data sheets that provide granular insights into product performance.
• Azure research reports and other PDF documents relevant to performance analytics.

To leverage this unstructured data, we adopted a sophisticated multi-agentic retrieval-augmented generation (RAG) framework built on these pillars:

• Knowledge Base Curation: This involved aggregating all relevant data reports, including performance dashboards, detailed KPI data, and research papers.
• Agentic RAG Framework: Designed to facilitate multi-step reasoning and intelligent query routing, this framework includes several key components:
• Brain/Routing: Manages intelligent routing of user queries to the appropriate agents.
• Performance Analytics Agent: Provides an overall performance overview of products, offering users a comprehensive view at a glance, helping users quickly identify the alarming stage.
• Insights Extraction Agent: This agent delivers detailed responses to specific queries by offering top key insights and recommendations through reasoning. It drills down into the data to extract actionable insights, making it easier for users to understand complex information and make informed decisions.
• RAG Agent: Handles queries related to research documents and general factual questions.

This structured approach ensures that users can seamlessly navigate and extract meaningful insights from complex and unstructured data.

By leveraging the multi-agentic RAG framework, users also benefit from intelligent query handling, comprehensive performance overviews and detailed insights. This makes data-driven decision-making more accessible, efficient, and effective.

Moving Beyond a Chatbot

The self-serve analytics solution enhances traditional chatbot capabilities by incorporating advanced functionalities. Powered by GenAI, it provides a centralized platform for users to access, understand, and derive insights from complex reports. Key components include:

• Signals 
• Function: Sends alerts to the team based on critical priorities.
• Purpose: Ensures the team is promptly informed about high-priority issues, enabling immediate action and response.
• Comprehension 
• Function: Provides deep dive analysis on the signals to identify potential root causes.
• Purpose: Goes beyond simple alerts by offering thorough analysis to understand underlying issues, facilitating more informed decision-making.
• Insights 
• Function: Generates tactical data insights.
• Purpose: Delivers valuable data-driven insights that support strategic planning and operational efficiency.
• Recommendations 
• Function: Offers actionable insights and suggestions to mitigate potential issues.
• Purpose: Helps address and resolve identified problems, preventing future occurrences.

The GenAI-powered self-serve analytics solution enables users to drill down into specific data points, receive recommendations, and ask real-time questions. It provides both a comprehensive overview and detailed insights into areas of interest, so data-driven decision-making becomes more accessible and efficient. By integrating these components, the self-serve Insights solution transcends the basic functionalities of a chatbot, offering a comprehensive solution for better decision making and operational management.