LLM Inference Cost Calculator: Model Monthly Cost Before You Launch
LLM inference cost is a non-linear function of token composition, model mix, and cache behavior — and almost no team models it before shipping. Plan it before the invoice arrives.
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Helpful resources & guides
A statically generated blog example with news, tutorials, resources and other interesting content related to AstroWind
LLM Model Selection Calculator for Quality, Latency, and Cost
Mid-tier models handle ~80% of production AI tasks at 25-35% the cost of frontier — and most teams have never benchmarked their workload to find out. Pick by task profile, not by brand.
NL-to-SQL Complexity Calculator: Decide if You Need an Agent
The same models that score 86% on Spider 1.0 score 10-17% on real enterprise schemas. NL-to-SQL is an architecture problem, not a model problem — here's how to scope yours.
RAG Chunking Calculator: Optimize Retrieval Quality and Cost
Most production RAG failures trace back to chunking — the upstream decision that gets the least architectural thought. Plan chunk size, overlap, and strategy before you embed 50GB the wrong way.
Why We Built superml.org: The SuperML Story
superml.org didn't come out of nowhere. It was built by the team at SuperML.org and SuperML.org — people who spend every day working with ML practitioners, developers, and AI researchers.
The Ontology Layer Every Enterprise AI System Needs (But Almost None Have)
Most enterprise AI systems fail in production not because the models are wrong, but because nobody defined what 'customer', 'transaction', or 'risk' means consistently across systems. This is a practical implementation guide for building the semantic layer that makes AI grounded, governed, and production-ready.