Apertis AI vs OpenRouter: Which AI API Gateway Should You Choose?
An honest comparison of Apertis AI and OpenRouter covering pricing, latency, features, and developer experience. Find out which platform fits your workflow.
RESEARCH
Apertis AI Research
Deep dives into AI infrastructure, API optimization, and practical insights for developers building with AI.
How to Cut Your AI API Costs by 60% Without Switching Models
Practical strategies to reduce AI API spending: prompt caching, context compression, model routing, and subscription plans. Real numbers and code examples included.
How to Use Claude Code with Apertis AI (Step-by-Step Setup)
Set up Claude Code to use any AI model through Apertis AI's API. Access Claude, GPT, Gemini, and 500+ models with one API key. 5-minute setup guide.
What is an AI API Gateway? A Complete Guide for Developers
Learn what an AI API gateway is, how it works, and why developers use platforms like Apertis AI to access 500+ AI models through a single API. Covers routing, failover, caching, and cost optimization.
RAFT: Retrieval-Augmented Fine-Tuning for Domain-Specific RAG
Master the RAFT technique to adapt language models for domain-specific question-answering with improved robustness to noisy retrieval results.
RuleRAG: Rule-Guided Retrieval-Augmented Generation for Knowledge-Intensive QA
Learn how to enhance RAG systems with logical rules to bridge semantic gaps and enable multi-hop reasoning.
Fine-tuning Embeddings with NUDGE: A Practical Implementation
Apply the NUDGE technique to optimize your embedding models for domain-specific retrieval without modifying model parameters.
Fine-tuning Gemma 2 with PEFT and LoRA
Master parameter-efficient fine-tuning techniques to adapt Gemma 2 without the computational cost of full model training.
Fine-tuning Gemma 2 9B: A Practical Guide
Learn how to efficiently fine-tune Google's Gemma 2 model for your specific tasks using modern techniques.
Multimodal Large Language Models: Architecture, Training & Data Strategies
Learn how MLLMs combine vision and language processing, including encoder design, modality interfaces, and training strategies.
What Matters in Transformers? Understanding Attention and Architecture
Explore which components of transformer architectures are truly essential and how you can optimize them for your use case.
Advanced RAG with Knowledge Graphs: Implementing Neo4j-Based Retrieval
Discover how to combine knowledge graphs with retrieval-augmented generation to create smarter, more structured question-answering systems.
NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
Learn how NUDGE enables efficient embedding fine-tuning without modifying model parameters, perfect for adapting retrieval systems to domain-specific data.