Zebra AI FAQ
Your questions our answers
Introduction and Getting Started
How does Zebra AI compare to Microsoft Copilot or OpenAI’s Data Analysis tools?
Zebra AI redefines data analysis by delivering instant, actionable insights with unparalleled efficiency. Unlike other AI tools, Zebra AI understands your business data intuitively, performing advanced calculations and extracting key drivers without manual prompting. In seconds, it generates professional, flexible, and deeply customizable visualizations, that adhere to industry standards like IBCS, while seamlessly integrating with PowerBI for easy access to all your data. With Zebra AI, there’s no need for complex data preparation – just upload your file and receive the insights you need to make smarter, faster decisions.
Beyond speed and automation, Zebra AI empowers your entire team to collaborate effortlessly. Its natural language follow-up capabilities and easy data story sharing allow colleagues, even without deep data knowledge, to engage with insights and ask the right questions. Coupled with flexible export options to Excel and PowerPoint, Zebra AI delivers a streamlined, user-friendly experience that not only saves time but drives business outcomes more effectively than other AI tools.
What kinds of analyses and visualizations can Zebra AI generate, and how interactive are they?
Zebra AI generates a variety of visualizations, including Pin charts, Line charts, Bar charts, Waterfall charts, and Integrated charts, based on the data uploaded. The pin and bar charts support one numerical measure at a time, while waterfall and line charts can display one or two measures. The integrated chart can handle up to two measures. The platform automatically identifies key trends and offers AI-driven business advice.
You can ask Zebra AI to generate specific charts using particular columns and filters, such as “Show me an integrated chart showing total sales this year vs last year by region”. Future updates will allow for more interactivity, including custom visual styles and multi-page dashboards.
Does Zebra AI support non-standard data formats, and how does it handle regional data differences (e.g., different date formats or currencies)?
Zebra AI supports various structured data formats but requires data to be in CSV, XLS, or XLSX for file uploads or integrated via Power BI connectors. If your data is in a non-standard format, pre-processing may be required to convert it into a supported format.
For regional differences, Zebra AI allows users to specify date formats, currency symbols, and decimal separators (e.g., comma vs. dot). Missing values should be represented as empty cells for optimal processing.
How do I get started with Zebra AI, and what are the steps for data upload and analysis?
Getting started with Zebra AI is simple:
- Register & Log In – Sign up using Microsoft or Google SSO.
- Upload Data – Upload a CSV, XLS, XLSX file (up to 50MB) or connect your Power BI dataset.
- Power BI (DAX API): Up to 15MB of data, 1 million cells, or 100k rows.
- Power BI (XMLA API, Premium workspaces): Up to 500MB
- For enterprise customers with Azure private hosting, this can be increased up to 10GB
- Automatic Analysis – Zebra AI processes your dataset and generates insightful dashboards with key trends, outliers, and variances.
- Explore & Customize – Ask follow-up questions, adjust filters, and customize visualizations.
Zebra AI supports:
- CSV, XLS, XLSX files (up to 50MB)
- A maximum of 25 columns is recommended for optimal performance.
General Formatting Guidelines:
- Column headers should be clear and meaningful (e.g., “Date,” “Country,” “Sales”).
- Ensure consistent formatting across all rows in a column.
CSV Files:
- Use comma-separated values.
- Numerical fields should use a dot (.) as the decimal separator and no thousands separator.
- Date or DateTime fields should follow a standard format (ISO 8601:
yyyy-MM-dd HH:mm:ss,MM/dd/yyyy, etc.).
Excel Files:
- The first table on the first sheet will be read.
- Headers should only be in the first row, with data starting from the second row.
- Missing values should be represented as empty cells.
- DateTime and numerical fields should be properly formatted in Excel.
Zebra AI has been tested and performs well with datasets containing up to 25 columns and 500k rows. While there are no strict limitations on the number of columns or rows, performance may vary for larger datasets, especially in terms of processing speed.
Features and Capabilities
Can I continue my analysis from where I left off in a previous session?
Yes, Zebra AI stores “stories” that include your chat history and generated dashboards in its database, but to resume the analysis, you need to reconnect the dataset. While Zebra AI does not learn from previous sessions or retain user-specific data, its built-in analytics and feedback loops help improve the tool at a product level. After an analysis session, new data cannot be added unless the session is restarted with a fresh dataset upload. Additionally, once a session ends, your data is permanently deleted from the server.
Can I customize Zebra AI to fit my business needs, including visual styles and corporate branding?
Yes, Zebra AI is customizable to meet the specific needs of businesses. Users can apply global filters, and customize visual styles, text fonts, and colors (including corporate branding). Future updates will offer more options for visual customization, such as multi-page dashboards and interactive elements. Users can also ask AI to focus on specific metrics or business needs, making Zebra AI highly adaptable to different industries.
You can also export analyses to PowerPoint (AI-generated titles, summaries, charts, and chat history) or Excel formats (images of the generated charts and the data slices used in the analysis) and further customize the presentation or sheet after export.
Can Zebra AI be accessed from mobile devices, and is there an option for offline analysis?
Currently, Zebra AI is accessible through web browsers on desktops and mobile devices, allowing users to interact with the platform on the go. The platform is optimized for mobile viewing, so users can upload data, ask questions, and review dashboards from their phones or tablets. However, offline analysis is not yet supported, as Zebra AI relies on cloud-based processing to perform data analysis and generate insights. Future releases may include offline capabilities or a mobile app to further enhance accessibility and productivity.
Can I track changes to my analyses or roll back to previous versions of dashboards in Zebra AI?
Zebra AI does not currently offer full version control, but users can review their previous analyses, charts, and stories through the “story” history feature. These stories, which contain dashboards, visualizations, and chat logs, can be revisited and shared. If users want to update or modify their analysis, they can re-upload the dataset and create a new dashboard while referencing previous stories.
Does Zebra AI support multi-language datasets and queries?
Currently, Zebra AI primarily conducts its initial analysis in English. However, you can ask questions in other languages. It also processes non-English datasets as long as the structure (e.g., column names) is compatible with standard formats.
Integration and Collaboration
How does Zebra AI integrate with other tools like PowerBI, and what future integrations are planned?
Zebra AI integrates with PowerBI, allowing users to connect datasets, run DAX queries, visually select required columns and measures, and import data for analysis. Free users can connect up to three datasets at a time, with additional connections available in higher subscription tiers. Future integrations will include SQL databases, cloud storage services, and other BI tools, making Zebra AI a flexible solution for businesses with diverse data needs.
Does Zebra AI offer on-premise deployment options and open-source AI models?
While Zebra AI doesn’t offer on-premise deployment, we do offer private hosting for enterprises that require additional data control. This allows businesses to deploy Zebra AI in a secure, dedicated cloud environment while maintaining the full functionality of the platform.
Currently, Zebra AI does not offer open-source AI models, but we continuously improve our algorithms based on industry best practices and user feedback.
For more details on enterprise solutions and private hosting, contact our team.
Can I share Zebra AI dashboards or reports with colleagues, and how can teams collaborate on data analysis?
Yes, Zebra AI provides robust sharing and collaboration capabilities. Users can share dashboards, “data stories”, with colleagues inside their organization. When sharing, colleagues can view the results, but to perform additional analyses or ask questions, they may need to reconnect the dataset. Shared dashboards and stories are saved securely in Zebra AI’s database, and each team member can independently explore the data or ask follow-up questions using the chat interface. Future updates will enhance these collaboration features, including real-time multi-user collaboration on the same datasets, similar to how teams work in tools like Google Docs.
Security and Privacy
How does Zebra AI ensure the accuracy of its insights and absence of hallucination, and can I validate or audit the AI’s decision-making process?
Zebra AI ensures the accuracy of its insights by using rigorous data processing and analysis techniques. It uses rigorous testing, data operation transparency, and logic-based algorithms to minimize hallucinations and improve accuracy. The platform performs automatic data cleaning, format checks, and consistency validations before conducting analysis. Additionally, users can validate AI-generated insights by reviewing the underlying data and statistical calculations that drive the visualizations using the “explanation” button.
What security measures are in place to protect my data when using Zebra AI?
Zebra AI takes data security seriously by implementing SSL/TLS encryption for data in transit and AES-256 encryption for data at rest. Uploaded data is only stored temporarily in the Azure cloud during the session, and it is permanently deleted once the session ends. Zebra AI does not use customer data for AI model training, and users’ personal information is protected in compliance with GDPR and other international data protection laws. Enterprise users also have the option to disable analytics tracking for added privacy. Personal data is only retained as long as necessary for providing services, and users have full control over their data. They can request access, correction, or deletion of their data at any time. Zebra AI also does not sell personal data to third parties.
How do you ensure the model isn’t trained using our data?
Zebra AI uses the OpenAI API Terms of Services, which guarantees that inputs and outputs are not used for training models. This ensures that your data is not stored or used to improve the underlying AI. Zebra AI minimizes the data sent to OpenAI by using server-side inference, descriptive statistics, and sampling. Additionally, no personal or contextual user data is passed through to OpenAI, ensuring your privacy.
How does Zebra AI ensure data security and privacy when collaborating or sharing datasets?
Zebra AI ensures data security and privacy through multiple layers of encryption and user permissions. All data is encrypted during transfer and at rest using industry-standard protocols, ensuring that it is protected from unauthorized access. When collaborating or sharing datasets, users can control access permissions, allowing only authorized colleagues from the same domain to view or interact with the data. Additionally, shared stories are stored securely in Zebra AI’s database, and any sensitive data is firewalled between users. Zebra AI complies with GDPR, ensuring that users can delete shared stories or restrict access as needed, further enhancing data privacy.
Pricing, Support, and Troubleshooting
What are Zebra AI’s pricing options, and how do they differ between free and paid tiers?
Zebra AI offers both free and paid tiers. Free users can access basic features, connect to 3 PowerBI datasets, and do only 5 AI interactions (initial analyses or extra queries users ask Zebra AI about their dataset) within a day, while paid tiers offer additional capabilities, such as more dataset connections, advanced sharing options, onboarding training and priority customer support. Users can upgrade or downgrade their subscription as needed, and refunds are available for early termination (with some restrictions). AI questions refer to the analysis or extra queries users ask Zebra AI about their dataset. The tool performs computations or additional analyses to answer these questions.
How user-friendly is Zebra AI, and what resources are available to help new users learn the platform?
Zebra AI is designed to be highly user-friendly, catering to both experienced data analysts and non-technical users. The platform uses natural language processing, so users can interact with Zebra AI by asking questions in plain English or any other language, making it intuitive for those without coding skills. For onboarding, Zebra AI offers various resources, including step-by-step guides, tutorial videos, and demo walkthroughs that help new users get familiar with key features. There are also live webinars and personalized onboarding sessions available for enterprise customers to ensure that teams get up to speed quickly.
How does Zebra AI maintain performance with large datasets or multiple concurrent users, and what are the limits for handling complex analysis?
Zebra AI is optimized for high performance, even with large datasets and multiple users. The platform uses cloud-based processing on Microsoft Azure, which enables it to scale resources dynamically based on data size and user activity. To maintain performance, Zebra AI limits individual dataset sizes to 50MB per upload and recommends keeping the number of columns in datasets to around 25 for the best experience. Zebra AI also continuously monitors system performance to identify bottlenecks and ensure the platform runs efficiently, regardless of data complexity.
How does Zebra AI handle user feedback, updates, and future feature requests?
Zebra AI values user feedback and continuously updates the platform based on customer needs and industry trends. Users can provide feedback on visualizations and AI-generated answers through features like the “dislike” button, which logs the issue for review and leaves feedback on the product. Zebra AI regularly releases updates, with upcoming features including enhanced AI engine capacity, corporate styling, and expanded dataset connections. Users can stay informed about updates through the Zebra AI newsletter. You can also check our Resource Hub for updates and news.
What should I do if I encounter issues or have questions while using Zebra AI?
Zebra AI leverages a variety of AI tools to analyze and answer questions about your data. However, due to the probabilistic nature of AI, it may sometimes select the wrong tool for a query, leading to an incorrect response. The main challenge lies in the wide variability of how data is structured in datasets, especially in Excel files. While Zebra AI can handle many cases, there are certain formatting requirements (see above). We’re also working on integrating a Data Cleaning AI engine to simplify this process.
You can improve the accuracy of results by asking for specific calculations or cleaning your data according to our guidelines. If you run into any issues, Zebra AI provides several support options. Free users can access the FAQ or submit support tickets via email at support@zebrabi.com, while paid users receive priority support with faster response times. We also use specialized error-tracking services to log and resolve any bugs or crashes quickly.