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Engineering Logs
Infrastructure updates, architecture decisions, and research from the NeuralRouting team on AI cost optimization, intelligent LLM routing, and reducing API spending for production systems.
We publish detailed benchmarks on how intelligent model routing reduces LLM inference costs by 70–85%. Our research covers model tier selection, prompt complexity scoring, and semantic caching strategies for production AI systems.
Deep-dives on building production-grade AI gateways — routing logic, fallback strategies, rate limiting, and observability. We cover OpenAI, Anthropic, and open-source model infrastructure.
Findings from running NeuralRouting at scale: cache hit rates, model quality audits, routing confidence matrices, and cost-per-request analytics across different product categories.