RAGnexus vs DATAKU

RAGnexus builds private AI assistants for European companies that need answers grounded in their own documents and systems. It connects to the tools where your knowledge already lives, indexes that content into a secure knowledge base, and deploys an assistant your team can query in natural language with cited sources.

The product is designed around data sovereignty. Deployments run on European infrastructure, with options that keep data off third-party model APIs entirely. RAGnexus targets regulated sectors like law, healthcare, and consulting, where confidentiality and GDPR compliance are non-negotiable.

Setup is handled as a managed service. RAGnexus integrates with your existing stack, handles indexing and maintenance, and delivers a working assistant in roughly four weeks for cloud deployments or eight to twelve weeks for fully sovereign on-premises setups.

DATAKU is a data science site that tracks AI benchmarks, API pricing, and model releases, then packages the numbers into free calculators and downloadable datasets. The homepage archives articles on inference costs, funding rounds, and head-to-head model comparisons, while the Tools section hosts eight utilities such as an LLM cost calculator, benchmark decoder, and model graveyard.

Most AI news sites summarize press releases. DATAKU cross-references provider docs, leaderboard scores, and its own pricing tables, which is why the downloadable datasets page lists 48-row pricing histories and 62-row benchmark score tables under CC BY 4.0 licenses.

Data analysts, ML engineers, and buyers use DATAKU when they need cost-per-token math, benchmark context, or CSV exports instead of marketing claims. The About page describes the project as benchmark and pricing tracking run by a former Tokyo data analyst.