Understanding Intent Classification with ONNX and DistilBERT

AI agents do not interact with enterprise APIs like traditional applications.
A conventional application follows predefined code paths. An autonomous agent interprets goals, reasons about available tools, creates requests dynamically, and may change its behavior when its model, prompt, context, or environment changes.
That creates a difficult question for every API request:
What is the agent actually trying to accomplish?
Synentra answers that question through real-time semantic intent classification. It combines a fine-tuned DistilBERT model with ONNX Runtime to classify requests locally, producing an intent label and confidence score before the request reaches the target API.
This article explains how that pipeline works, why Synentra uses DistilBERT and ONNX Runtime, how confidence affects governance decisions, and how you can train and deploy a model for your own domain.


