AI Engineering

8 articles in AI Engineering

Inside DeepQuantica: Our Foundational Code & Backend for Training ML and LLMs

A transparent look at the engineering stack, training infrastructure, and backend architecture we use to build and deploy production AI systems. No black boxes.

16 min read

The Complete Guide to Production LLM Deployment: From Fine-Tuning to Monitoring

Everything you need to know about deploying large language models in production - inference optimization, scaling, monitoring, and best practices from 100+ deployments.

16 min read

Building Production LLM Applications: RAG, Agents, and Fine-Tuning Patterns

Practical patterns for building LLM-powered applications that work in production. Covering RAG architecture, AI agents, fine-tuning strategies, and when to use each approach.

17 min read

PEFT Explained: Parameter-Efficient Fine-Tuning Techniques for LLMs

A complete guide to Parameter-Efficient Fine-Tuning (PEFT) methods including LoRA, QLoRA, Prefix Tuning, and Adapters. How they work and when to use each one.

14 min read

Auto Deployment for ML Models: From Training to Production in Minutes

How auto deployment works for machine learning models. Learn how SnapML automates containerization, scaling, API generation, and monitoring for production ML deployment.

12 min read

How to Deploy LLMs in Production: Inference Optimization, Scaling, and Monitoring

A practical guide to deploying large language models in production. Covers inference engines, quantization, auto-scaling, caching strategies, and real-time monitoring with SnapML.

15 min read

Best ML Deployment Platforms in 2026: From Model to Production API

Comparing the top platforms for deploying machine learning models to production in 2026. SnapML, BentoML, Seldon Core, cloud services, and more.

12 min read

Fine-Tuning vs RAG: When to Fine-Tune Your LLM and When to Use Retrieval-Augmented Generation

A practical comparison of fine-tuning and RAG for LLM applications. Learn when each approach works best, when to combine them, and how SnapML supports both workflows.

15 min read

AI Engineering Articles on DeepQuantica Blog - AI Engineering, Machine Learning, Auto ML, Auto LLM

Browse 8+ articles about AI Engineering on the DeepQuantica blog. DeepQuantica is an AI engineering company and creators of SnapML, the unified AI platform with Auto ML and Auto LLM capabilities. Read expert insights about machine learning, deep learning, LLM fine-tuning, MLOps, and production AI deployment.