Free AI Text Classifier – Multi-Class Intent, Ticket Category & Topic Categorizer
The NexVaani AI Multi-Class Text Intent Classifier enables customer support managers, product teams, and data analysts to categorize incoming textual data automatically. With support for custom category taxonomies and trigger keywords, evaluate support tickets, customer reviews, and feedback submissions in milliseconds. Review confidence score distributions and export classification logs directly in your browser with zero data leakage.
The NexVaani AI Text Classifier categorizes text submissions across custom classes such as Billing, Technical Bugs, Feature Requests, and Feedback with real-time confidence scores and zero server uploads.
AI Multi-Class Text Intent Classifier
Categorize support tickets, emails, and user queries with customizable category ontology.
Real-World Use Cases & Applications
- Automatically routing customer support tickets to the appropriate department.
- Categorizing user app reviews into bug reports, feature requests, or praise.
- Filtering spam and high-priority escalation inquiries in incoming email batches.
- Analyzing survey responses and customer sentiment trends across structured categories.
NexVaani Tool Transparency
Technical breakdown of processing location, network behavior, and data retention
Supported tools execute locally in your web browser using client-side technologies.
Calculations and text transformations are performed locally in your browser.
Temporary processing data is handled locally by your browser and is not stored by NexVaani.
No watermark, stamp, or branding is added to the exported file. Output quality depends on your source file and selected settings.
How to Use AI Multi-Class Text Intent Classifier (Step-by-Step)
Paste Text Input
Enter or paste the ticket, feedback, or review text.
Customize Categories
Adjust category names and trigger keywords to match your workflow.
Review Intent Match
Inspect the predicted primary category and confidence percentage.
Export Classification
Copy the analysis or download the structured JSON report.
Technical Architecture & Execution Mechanics
Multinomial Naive Bayes & Softmax Probability Distribution
Classification calculates posterior probabilities across class set $C$: $P(c | d) \propto P(c) \prod_{k} P(t_k | c)$. Normalized confidence percentages are derived via the softmax activation function: $\sigma(z_i) = \frac{e^{z_i}}{\sum_{j=1}^K e^{z_j}}$.
P(c_i | \mathbf{x}) = \frac{\exp(\mathbf{w}_i^T \mathbf{x})}{\sum_{j=1}^K \exp(\mathbf{w}_j^T \mathbf{x})}Technical Limitations & Operational Constraints
- Text with multiple conflicting intents will show balanced confidence scores across multiple categories.
Key Specifications & Capabilities
- Custom Category Ontology – Add, remove, and configure target categories and keywords
- Confidence Distribution Bars – Visual breakdown of percentage probability across all classes
- Key Trigger Highlighting – Inspect exact matched keywords that influenced classification
- Structured JSON Export – Download classified results formatted for CRM and ticketing integration
Frequently Asked Questions & Answers
Can I add my own custom categories?
Yes! You can add unlimited custom categories and define specific trigger keywords for your industry.
Does this tool store my customer's private data?
No. All text parsing runs client-side in your browser memory without storing or logging anything.
Are my files uploaded, analyzed, or stored on NexVaani servers?
Where supported, tool inputs and files are processed locally inside your web browser using WebAssembly and HTML5 Canvas. Your files are not uploaded to NexVaani file-processing servers.
Rate AI Multi-Class Text Intent Classifier
Current Community Rating: 4.8 / 5.0 (1,420 verified reviews)
Every formula, algorithm, and WebAssembly execution path is verified for client-side sandbox isolation, numeric accuracy, and zero server file transfers.
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