Hello everyone,
I’m working on a Blazor web application that allows users to upload time-series data, which then gets visualized dynamically using Syncfusion’s Spreadsheet and Chart components. The goal is to let users apply simple data transformations, filters, and then generate interactive charts in the browser.
My twist: I’m experimenting with using artificial intelligence to automatically detect trends, anomalies, or outliers in the data before rendering charts. For instance, after the user uploads a CSV file, an AI model flags suspicious spikes or seasonal patterns, and we highlight them visually in the spreadsheet and chart.
In particular, I’m using Syncfusion’s Blazor Spreadsheet component to render the data grid, then overlaying colored annotations where the AI model flags anomalies. Attached charts display trend lines and forecasted values derived from the AI analysis.
So I’m curious: how would others approach integrating server-side AI models with Syncfusion’s components? Has anyone built a similar workflow—upload → analyze → visualize using Syncfusion UI—perhaps using Azure AI or TensorFlow.net? Any guidance on best practices for combining Syncfusion controls with an AI‑powered backend would be really helpful!
Thanks in advance for sharing your wisdom, and eager to learn from your experiences!