
Modern enterprises face challenges caused by ever growing volume of data they need to process and analyze. Business users such as sales managers often rely on technical competencies of other people to make sense out of enormous spreadsheets in order to analyze data and draw the insights they need. The process becomes even more complex, in a constantly changing environment and cross-team collaboration. 

To address these challenges, [DIAL eXpressive Logic (XL)](https://xl.dialx.ai/) can be leveraged as an AI-powered data platform designed to democratize natural language access to structured data. DIAL XL empowers both business and power users to rapidly ideate, explore, and analyze sales data in real time, fostering a collaborative environment.

Key highlights:

- **Handling Large-Scale Datasets**: DIAL XL enables the analysis of large datasets with millions of rows of sales data, such as details about branches, cities, costs, and customers (age, gender, etc.) and more.
- **Natural Language Queries**: Users can query the dataset directly by asking questions in natural language. For example, "What is the branch that generates the highest revenue?" DIAL XL's agents then execute the query, generate and add the necessary artifacts to the spreadsheet, which can be used as an input for further analysis.
- **Executive Dashboard and Reports**: You can prepare read-only dashboards and reports for executive users based on your projects, who can then use them to explore data using only natural language.
- **Data Visualization**: DIAL XL users can visualize data by creating and inserting graphs and charts into spreadsheets using commands in natural language. An agent that processes a request can automatically assess it and render the output as charts or graphs when it is needed for better visibility. Generated artifacts, such as new tables and charts, can then be used as an input for further analysis.
- **Enhanced Data Integration**: Agents combine semantic indexation of the available datasets and leverage powerful language models to add data that is not available in the spreadsheet, enriching the analysis and providing deeper insights. Agents understand the context and automatically take into consideration both original datasets and newly generated ones when processing requests.
- **Data Validation and Transparency**: Users can preview the steps and reasoning behind each agent's action, ensuring transparency and accuracy. For all calculations, DIAL XL uses user-friendly formulas accessible even for non-technical users.
- **Real-Time Collaboration**: Teams can collaborate in real time, sharing projects with or without editing rights. When multiple users are working on the shared project, changes apply for all users simultaneously in real time.

Outcomes and Benefits:

DIAL XL brings data accessibility to the next level empowering business users to do research and analyze sales data with self-sufficiency using only natural language, leading to lower barriers to working with data for a wider range of users. Real-time collaboration allows building a more agile team environment, enabling rapid ideation and exploration of data.



Empower business users to easily explore large-scale sales data at a professional level using natural language.

Sales Data Analysis


Business users, like sales and supply chain managers, often struggle to process and analyze large datasets. Extracting key insights—such as order conversion rates, inventory turnover, demand fluctuations, and forecasting—can be challenging, especially when dealing with complex or overwhelming volumes of information. Traditional BI tools often require technical expertise, making it difficult for these stakeholders to quickly obtain actionable information to make timely and data-driven decisions. 

To address these challenges, DIAL offers an open, flexible, and [feature-rich platform](/platform) that can be integrated with the existing software ecosystem and data sources. It provides all the necessary tools and technologies to create powerful, goal-oriented solutions that meet the specific needs of the business and are intuitive for both power and business users.

In this case study, we describe our multi-agent application for supply chain managers which enables them to work, analyze and interpret sales data stored in database to analyze orders conversion rates using only natural language.

Key highlights:

- **Integration with Corporate Data**: We created a dedicated [multi-agent application](/agentic-platform), that can draw data from the corporate Databricks Lakehouse by transforming requests from business users in natural language into SQL queries and returning answers as narrative explanations and data visualizations.
- **Data Validation and Transparency**: Users can preview the steps and reasoning behind each agent's action, ensuring transparency and accuracy.
- **Structured and Unstructured Data**: The application uses [DIAL RAG](https://github.com/epam/ai-dial-rag) as an agent to upload and analyze files in addition to the data extracted from the data storage. The context is preserved throughout the conversation, enabling the combination of findings from the SQL database and uploaded files to generate rich visualizations and analytics.

Outcomes and Benefits:

The implemented solution can bring significant benefits for a retail enterprise by improving data accessibility and enabling research and analysis for non-technical users. The application quickly transforms raw information into actionable insights using natural language queries and AI agents, enabling business users to easily explore data, uncover trends, and draw insights. Intuitive and dynamic visualizations further enhance data exploration and analysis.



Empower supply chain managers to explore order conversion rates, make sales, demand or inventory analysis with intuitive AI-powered solutions.

Supply Chain Analytics


In today's competitive retail environment, businesses strive to attract and retain customers by continually enhancing shopping experience, delivering customized and personalized interactions powered by cutting-edge technologies.

[DIAL platform](/platform) offers an enterprise-grade ecosystem of AI-powered tools and services designed to streamline research and development of GenAI solutions for the retail business. 

With DIAL, you can create powerful [multi-agent applications](/agentic-platform), such as AI shopping assistants, that integrate seamlessly into your existing products, ensuring a cohesive and consistent branding and user experience.

Features and Benefits of AI-Powered Shopping Assistants:

- **Uninterrupted Assistance**: AI-powered assistants can mimic a real person and provide uninterrupted service, offering technical support, sales assistance, and customer service around the clock, especially during peak hours. This ensures consistent and high-quality customer service, improving overall satisfaction.
- **Personalized Shopping Experience**: By guiding customers through complex product selections and personalized sales journeys, the assistant can enhance the overall shopping experience, making it more tailored and engaging.
- **Product Demos and Interactive Training**: The assistant can offer expert demos, interactive training, and edu-tainment experiences to educate customers about products and services, helping them make informed purchasing decisions. By integrating with databases and utilizing [RAG](https://github.com/epam/ai-dial-rag), it ensures consistent, reliable, and accurate responses about the company and its products, reducing hallucinations and providing more deterministic information.
- **Quick Actions**: Apps developed with DIAL can easily integrate with external services to perform tasks like placing orders and retrieving user information. This allows the assistant to handle actions such as proceeding to checkout directly within the chat bot, making the shopping process faster and more convenient without requiring users to navigate elsewhere.
- **Security and Privacy**: DIAL enables the creation of compliant and secure applications by helping meet privacy and regulatory requirements for PII. It includes [tools for placing guardrails](https://docs.dialx.ai/video%20demos/Developers/interceptors), obfuscating PII, blocking specific content, and more, ensuring a secure shopping experience and maintaining trust and compliance.



Bring user experience and customer service to the next level with AI-powered assistants.

Retail & CPG

Sales Data Analysis

Supply Chain Analytics

AI Shopping Assistant