Blog
Practical guides on LLM routing, RAG, batch inference, and building production AI apps without managing infrastructure.
LangChain is a framework you host and maintain. Here's how to build a multi-model AI app — routing across Claude, GPT, and Llama — with a managed REST API instead.
Read more →A complete guide to integrating Neureus AI into a Next.js 15 App Router project — streaming chat, RAG, and server actions. Production patterns, not toy examples.
Read more →OpenAI's Batch API charges 50% of realtime rates. Neureus adds another 40% off on top. Here's how to identify workloads that are safe to batch and implement it in under 30 minutes.
Read more →The direct OpenAI SDK is the right default. Here's the exact moment it stops being enough — and what you get when you switch to Neureus.
Read more →A complete customer support bot using Neureus: ingest your docs, add semantic search, stream responses, and handle escalation — under 100 lines of TypeScript.
Read more →Retrieval-Augmented Generation doesn't require a vector database, embedding service, or LLM orchestration library. Here's a complete RAG app in 50 lines of TypeScript.
Read more →Neureus tokens always cost 10% less than OpenRouter. Here's the mechanism that makes it possible: a 4-pass prompt preprocessor that cuts token count before provider billing.
Read more →Most teams running AI in production are paying for 5 separate services that could be one API call. Here's the breakdown of where the money goes and how to cut it by 80%.
Read more →Single LLM calls solve simple problems. Complex workflows need patterns: ensemble voting, step-back reasoning, expert routing, and more. Here's how to implement them as API calls.
Read more →Model Context Protocol (MCP) and REST APIs solve different problems. Here's when to expose your product via MCP, when to stick with REST, and how Neureus supports both.
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