ChatBI lets users retrieve data instantly using natural language. This question-and-answer approach allows anyone to analyze data, pioneering a new form of data consumption.
ChatBI is a value-added module and requires a separate purchase. After purchase, an organization administrator can assign a seat to members on the member management page. Users without an assigned seat cannot use ChatBI features. For detailed instructions, see Manage Organization Users.
ChatBI is available only for Quick BI Advanced and Professional editions. It is not supported in the Personal edition.
To embed ChatBI into your business systems, you must purchase the Ticket-enhanced embedding module. This module is available only for the Professional edition and above.
Core advantages
Efficiently retrieve data through a question-and-answer format, reducing the workload of manual data extraction.
Uncover the root causes of data anomalies and fluctuations to simplify decision-making.
Anomaly detection:
Identifies anomalies from reports or data files and automatically drills down to find their source in more fine-grained objects. For example, it can trace a monthly profit anomaly back to specific customers.
Fluctuation attribution:
Compares metric fluctuations over different time periods and analyzes the contributing factors from various perspectives. It highlights the contribution of each factor to help you pinpoint the cause and determine a course of action.
Custom contextual insights:
Integrates with custom Agents built on platforms like Dify or Model Studio. Create custom workflows to connect ChatBI to specific business scenarios and gain contextual insights.
Supports complex query scenarios, including multi-turn conversations.
Use cases
With its natural language Q&A capabilities, ChatBI accelerates data retrieval, reduces the burden of manual queries, and automatically detects data anomalies to pinpoint root causes. By comparing metrics across different periods, ChatBI performs fluctuation attribution analysis, breaking down the contribution of each dimension to clarify the reasons behind changes. This makes it ideal for high-frequency, data-driven decision-making scenarios such as business performance analysis, operational reviews, and issue troubleshooting.
Scenario 1: Business management
Scenario description: Use AI+BI to improve business management efficiency and uncover opportunities for profit growth.
Comparison: The following table compares traditional data analysis methods with the capabilities of ChatBI in this scenario.
Traditional approach (before)
Intelligent approach (after)
Heavy reliance on manual sales analysis.
Sales report analysis: Relies on manual work. Dozens of people gather nightly to review sales reports. The lack of tools for both fixed and flexible analysis means they can only filter a single report repeatedly, leading to inefficient weekly business reviews.
Sales issue review: Relies on meetings. Data analysis across customers, orders, and categories depends on individual expertise. This often leads to missed management insights and makes it difficult to learn from others' sales experience.
Market trend tracking: Relies on experience. Manually recorded sales notes cannot be linked with performance data. Sales goal attainment depends entirely on human supervision, with no closed-loop monitoring from targets to actions.
AI-assisted business management enables efficient and precise decisions anytime, anywhere.
Interactive queries: Conduct intelligent sales reviews. Get performance data quickly through conversations and receive further suggestions from the AI large model.
Interaction summary: Intelligent Sales Quality Inspection uses large AI models, letting you customize customer analysis models to find opportunities and risks in sales visit records.
Periodic reports: Make intelligent business decisions. Use an Agent for intent classification to support conversational daily report attribution. Leverage the Agent's auto-planning capabilities for weekly business analysis.
Summary: AI-powered insights provide a comprehensive overview of sales management progress, making performance growth trackable, manageable, and predictable.
More efficient: Self-service data queries and automated progress summaries improve daily operational efficiency by 80% and reduce unnecessary discussions by 50%.
Easier to manage: Relieves sales and business managers of sifting through hundreds of reports, allowing them to focus on core tasks like customer management and performance goals to drive business growth.
Scenario 2: Supply chain management
Scenario description: Use AI+BI to boost operational analysis efficiency and identify opportunities for supply chain optimization.
Comparison: The following table compares traditional data analysis methods with the capabilities of ChatBI in this scenario.
Traditional approach (before)
Intelligent approach (after)
Tedious manual analysis and discussions.
Multi-dimensional supply chain analysis: Relies on manual work. Business analysis involves numerous drill-down dimensions, making fixed reports insufficient (<20% coverage). Data is needed on a flexible timeline, but manual data extraction is slow and costly, with reports often available only weekly.
Order delay root cause analysis: Relies on meetings. The lack of multi-dimensional target variance analysis makes it difficult to pinpoint core issues among hundreds of dimension combinations. Manual analysis is inaccurate and inefficient.
Problem resolution: Relies on asking others. Staff must rely on offline documents and training to look up business terms. This results in slow onboarding, high training costs, and inconsistent information across teams.
AI-assisted supply chain management provides instant answers to efficiently identify root causes and guide actions.
Insights: Intelligently track performance goals. Use topic-based conversational queries to "consume" data. For example, ask "What is the order fulfillment performance in each region?" and get an instant chart showing the underlying reasons.
Diagnostics: Intelligently analyze abnormal nodes and causes. The AI assistant provides smart analysis and automatic attribution. Simply ask, "What are the core reasons for the Northeast region's failure to meet its fulfillment rate this week?"
Actions: Intelligently retrieve related knowledge. An AI-powered knowledge platform provides a centralized, searchable repository, allowing all staff to quickly access information and stay aligned.
Summary: AI-powered attribution efficiently identifies supply chain fulfillment issues, making the entire operational chain diagnosable, scalable, and reliable.
More efficient: Automated information retrieval and Q&A improve daily operational efficiency by 80% and reduce manual work by 30%.
Easier to manage: Proactively identifying issues lets business staff focus on core tasks like fulfillment and inventory control, which reduces operational costs.
Features
In the ChatBI interface on PC or mobile, you can preview and select datasets, ask questions in the input box or use Quick Questions, engage in multi-turn conversations, and review past conversations in the Conversation List.
Diverse data sources
Supports querying a dataset or an uploaded data file.
Convenient query methods
Supports typing questions directly or using more efficient methods like Quick Questions and Voice Input.
Diverse large model options
Supports using the system's built-in large model or a custom large model for interpretation and reasoning.
Data insights and fluctuation attribution
Compares metric fluctuations over different time periods and analyzes the contributing factors from various perspectives. This helps you pinpoint the cause and determine a course of action.
Predictive data trends
Forecasts future trends based on historical data.
Traceable conversation history
Displays your conversations from the last 30 days.
Multi-device compatibility
Supports asking questions on mobile phones and tablets.
Workflow
The following table outlines the ChatBI workflow and provides links to relevant documentation.
Step | Action | Description |
1 | Data preparation | Before you can use ChatBI, you must configure your dataset for natural language queries. For more information, see Data Preparation. |
2 | Flexible configuration and management |
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3 | Start a chat | Once preparation is complete, authorized users can start a conversation in the ChatBI interface to:
For more information, see Start a Chat. |
4 | ChatBI operations | As users interact with ChatBI, the system logs their query activities. You can select specific interactions from these logs to track as a use case. For more information, see ChatBI Operations. |
5 | System integration | With Quick BI Professional edition, you can use the Ticket-enhanced embedding solution for ChatBI to enable secure, one-stop management of links, access, and queries. This helps you integrate ChatBI into your business systems at a low cost and build data products with your own branding. For more information, see Quick BI ChatBI Embedding. |
Trial and inquiries
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