Production AI engineering guides.
Long-form playbooks on the topics that actually decide whether your AI feature ships profitably. Cost, architecture, compliance, multimodal — each guide is the canonical Kunavo answer plus links to every supporting deep dive.
- Cost·11 min read
AI cost optimization — the complete guide to cutting 70-90% off your LLM bill
If you're paying more than $1,000/month on LLM APIs, this guide will save you at least half. Every technique is published with measured savings and runnable code. Stack 3-5 of them and 70% reduction is realistic without quality tradeoff.
Read guide - Architecture·14 min read
RAG implementation guide — production retrieval-augmented generation with Claude and Gemini
Build a production RAG system that actually works — not just a 100-line demo. Covers chunking strategy, embedding model choice, retrieval ranking, prompt structure, hallucination control, and how to keep monthly costs in three figures even at 10,000 queries/day.
Read guide - Compliance·12 min read
AI compliance guide — GDPR, DSGVO, RGPD, LGPD, KVKK and Japan's tokutei-shoutorihiki
Shipping AI in production means meeting the data-protection regime of every country you sell to. This guide is the practical playbook — what each regulator actually checks, what Kunavo provides under our DPA, and what you still need to do on your side.
Read guide - Multimodal·10 min read
Multimodal AI guide — text, image, video and audio under one OpenAI-compatible API
Most aggregators only cover text. Kunavo gives you image (Nano Banana, GPT-Image, Flux, Seedream), video (Veo 3, Sora, Seedance), audio (ElevenLabs, Suno) on the same API. This guide is when to use which, and how to chain them for production-grade multimodal workflows.
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