What are The Challenges of Building Your Own AI Assistant?
Like all technology, implementing AI analytics assistants for embedded analytics comes with its share of challenges. Some companies attempt to create their own AI analytics assistant using GPT-based APIs, only to waste valuable resources in the process.
Developing a custom assistant comes with numerous challenges, such as handling massive datasets, supporting multi-tenancy architecture, ensuring robust security and governance, catering to diverse user needs, and integrating with existing systems.
To be fair, it’s not easy to create a system that can query correctly from a large database – with billions of rows of data as well as support a multi-tenant architecture and guarantee full privacy among users. So an alternative (that saves time) is to embed an external solution within your software. Veezoo is able to handle all the above challenges with ease, as it has an architecture that was built for this purpose.
Let’s focus on the size of the dataset first. Handling massive datasets with billions of rows of data is a major challenge when implementing AI analytics. New startups are trying to leverage GPT for this purpose – but often they run into issues since GPT was not designed to handle billions of rows of data in their prompts. Thus, people need to really limit themselves. But Veezoo’s AI analytics assistant is designed to handle complex queries and large datasets, ensuring seamless scalability and performance.
Supporting a multi-tenant architecture that allows multiple users to access the same AI analytics solution securely and efficiently is another challenge. Building such an architecture requires careful planning, robust security measures, and efficient resource allocation to cater to the varying needs of different users. This often leads to delays and lagging timelines and is one of the major challenges associated with building this technology in-house. But it’s also a compelling argument for going for an external solution that handles this with ease.
Another challenge in the same vein is catering to diverse user needs and integrating with existing systems are also significant challenges when implementing AI analytics for embedded systems. Veezoo provides a user-friendly interface that caters to diverse user needs and offers seamless integration with existing systems.
Despite all of these challenges, more and more software providers are choosing to have an AI analytics assistant within their platforms today.
Advantages of AI Analytics Assistants for Embedded Analytics
Want to know why? Because the advantages really do make it worth the trouble.
Here are some significant advantages of having embedded analytics within your platform:
1. Empower end-users with better access to information: The beauty of embedded analytics lies in its ability to provide end-users with the information they need almost instantly. This helps them make fact-based decisions very easily, without having to wait on a data team for days. Moreover, since it integrates with existing business applications seamlessly, users can access data insights without having to switch between different software platforms, promoting efficiency and productivity. Lastly, since most external solutions can be white-labeled and customized, users have a native experience within the software. It’s a win-win!
2. Clean and Easy-to-Navigate User Interface (UI): A well-designed UI is crucial to make the most out of any technology, and embedded analytics is no exception. AI analytics assistants help create a clean and intuitive interface, making it easy for users to ask questions, explore data, and interpret results. Product managers can finally say goodbye for good to adding yet another dashboard or report to their interface. This enhances user engagement and facilitates better data-driven decision-making.
3. Saving Time and Focusing on Core Competency: By integrating AI analytics assistants into their business applications, organizations can save significant time spent on perfecting the data experience within their tool, which may not necessarily be a part of their core competency. They can instead perfect their tool’s offerings and focus on making it even better.
The Future of Embedded Analytics
In a world where data is the new oil, embedded AI Analytics assistants like Veezoo is the high-performance engine that helps every user unlock the true potential of their data with ease. It’s not just about making sense of the data; it’s about making the data work for you. With Veezoo, businesses can look forward to a future where data analysis is not just a function, but an integral part of their operations.
A future where every decision is data-driven, every process is optimized, and every outcome is improved.