Integrating LLM with Other Machine Learning Models

We are building a support ticket intelligence pipeline that classifies incoming requests and drafts contextual replies by combining Oxlo.ai embeddings

giovedì 18 giugno 2026 New tab

774 words~4 min read

We are building a support ticket intelligence pipeline that classifies incoming requests and drafts contextual replies by combining Oxlo.ai embeddings, a local random forest classifier, and an LLM. It helps support teams cut response time by automating triage and surfacing relevant historical resolutions. The entire stack runs through Oxlo.ai's OpenAI-compatible API, so we can standardize on one provider for both vector and text generation workloads.

What you'll need

Python 3.10+

An Oxlo.ai API key from https://portal.oxlo.ai

The OpenAI SDK and scikit-learn: pip install openai scikit-learn numpy

Integrating LLM with Other Machine Learning Models

Integrating LLM with Other Machine Learning Models

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Related reading

The Future of Large Language Models

Open Source and In-House: How Uber Optimizes LLM Training

Advantages and Disadvantages of Using LLM

Best LLM Models for Conversational AI in Language Learning

Enterprise-grade AI integration: embedding LLMs into the business processes of…

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