Swiggy's Hermes: Revolutionizing Data Access with Generative AI

In today's data-driven landscape, Swiggy, a leading Indian food delivery service, is leveraging the power of generative AI through its innovative tool, Hermes. Designed to accelerate data access and interpretation, Hermes empowers Swiggy's diverse teams to make faster, more informed decisions. Unlike many AI tools focused on text summarization, Hermes excels at delivering precise numerical data and detailed insights crucial for business strategy. Whether assessing the impact of a network outage or analyzing customer feedback, Hermes enables Swiggy employees to pose natural language questions and receive immediate SQL queries and results within Slack. This eliminates the need for extensive technical expertise, democratizing data access across the organization.

Key Features of Hermes:

• Streamlines data access and interpretation for all teams.
• Facilitates natural language queries with instant SQL query and result delivery in Slack.
• Hermes V2, the latest iteration, employs a compartmentalized approach for improved accuracy and efficiency.
• Leverages a Knowledge Base and Retrieval-Augmented Generation (RAG) for enhanced contextual understanding.
• Widely adopted across Swiggy, significantly reducing data retrieval time.
• Empowers diverse teams, including product managers, data scientists, and analysts, with minimal technical barriers.

Table of Contents:

• Swiggy's Data Challenge
• Hermes V1: The Initial Implementation
• Hermes V2: Enhancements and Refinements
• The Generative AI Model Pipeline
• The Refined Model Pipeline
• The Future of Hermes at Swiggy
• Our Perspective
• Frequently Asked Questions

Swiggy's Data Challenge:

Swiggy faced a common organizational hurdle: providing seamless data access to employees across various departments without relying heavily on technical specialists. Traditional methods, involving complex SQL queries and analyst intervention, proved time-consuming and inefficient, hindering timely decision-making.

Hermes V1: A Solid Foundation:

The first version of Hermes utilized GPT-3.5 variants. While successful, it highlighted the need for a more tailored solution to handle complex queries and large datasets. This led to a key design shift: compartmentalizing Hermes into distinct business units ("charters"), each with its own metadata and specific use cases.

Hermes V2: A More Refined Approach:

Hermes V2 addresses the limitations of its predecessor with a refined architecture:

• User Interface: Slack remains the primary interface for querying and receiving results.
• Middleware (AWS Lambda): Handles communication between the user interface and the AI model.
• Generative AI Model: Generates SQL queries and executes them via Databricks jobs.
• Knowledge Base RAG: Provides crucial context and ensures accurate query generation.

The Generative AI Model Pipeline:

Hermes V2's core strength lies in its Knowledge Base and RAG approach. This allows the model to understand Swiggy's specific data structures and generate accurate SQL queries.

The Knowledge Base is crucial for contextual understanding, disambiguation, accuracy, and scalability.

The Refined Model Pipeline:

The improved pipeline in Hermes V2 breaks down user prompts into stages:

1. Metrics Retrieval: Identifies relevant metrics.
2. Table and Column Retrieval: Locates necessary tables and columns.
3. Few-Shot SQL Retrieval: Uses reference queries to guide generation.
4. Structured Prompt Creation: Compiles information for the LLM.
5. Query Validation: Validates and corrects SQL queries.

Adoption and Impact:

Hermes has been widely adopted, processing thousands of queries daily with an average response time under two minutes. Its impact spans across various teams, significantly boosting productivity and data-driven decision-making.

The Future of Hermes at Swiggy:

Swiggy continues to refine Hermes, incorporating user feedback and pushing the boundaries of AI-powered data accessibility.

Our Perspective:

Swiggy's Hermes exemplifies the transformative potential of generative AI in data management. Its tailored approach showcases how AI can empower teams and enhance operational efficiency.

Conclusion:

Swiggy's success with Hermes highlights the importance of accessible and actionable data. Hermes V2 sets a new standard for democratizing data access and accelerating decision-making.

(Frequently Asked Questions section remains the same as in the original input.)

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