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<rss version="2.0"><channel><title>Alectura Labs engineering notes</title><link>https://alecturalabs.com/blogs</link><description>Practical guides for AI product and enterprise engineering teams.</description><item><title>LLM data residency: an engineering checklist</title><link>https://alecturalabs.com/blogs/llm-data-residency-processing-storage-fallback</link><guid isPermaLink="true">https://alecturalabs.com/blogs/llm-data-residency-processing-storage-fallback</guid><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate><description>A practical review of inference locations, stored content and fallback paths for enterprise AI teams assessing LLM data residency requirements.</description></item><item><title>Per-customer LLM policies for SaaS</title><link>https://alecturalabs.com/blogs/per-customer-llm-policies</link><guid isPermaLink="true">https://alecturalabs.com/blogs/per-customer-llm-policies</guid><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate><description>A practical design for customer-specific model access, processing regions and retention, including policy conflicts, fallback and request evidence.</description></item><item><title>Per-user LLM spend limits under concurrency</title><link>https://alecturalabs.com/blogs/per-user-llm-spend-limits-concurrent-requests</link><guid isPermaLink="true">https://alecturalabs.com/blogs/per-user-llm-spend-limits-concurrent-requests</guid><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate><description>Design LLM budgets around reservations, settlement and failure recovery so parallel requests do not all spend the same remaining allowance.</description></item><item><title>PII redaction vs pseudonymization for LLMs</title><link>https://alecturalabs.com/blogs/pii-redaction-vs-pseudonymization-llm</link><guid isPermaLink="true">https://alecturalabs.com/blogs/pii-redaction-vs-pseudonymization-llm</guid><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate><description>Choose between removing personal data and replacing it with reversible stand-ins, with examples, isolation requirements and tests for internal AI tools.</description></item></channel></rss>
