<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Antenor Blog</title><description>Field notes on operations AI: route optimization, forecasting, simulation, RAG and automation, written by the engineers who ship it.</description><link>https://antenor.ai/</link><language>en-us</language><item><title>We Built RAG Before It Was Called RAG</title><link>https://antenor.ai/blog/rag-before-rag-legal-retrieval/</link><guid isPermaLink="true">https://antenor.ai/blog/rag-before-rag-legal-retrieval/</guid><description>Decades before large language models, we built XLBase — a proprietary retrieval engine — and the legal case-law system on it acquired by Jurisprudencia Argentina. What that experience teaches about building RAG that actually works today.</description><pubDate>Sun, 05 Jul 2026 00:00:00 GMT</pubDate><category>rag</category><category>enterprise-search</category><category>legal</category></item><item><title>Do You Actually Need a Bigger Warehouse?</title><link>https://antenor.ai/blog/do-you-need-a-bigger-warehouse/</link><guid isPermaLink="true">https://antenor.ai/blog/do-you-need-a-bigger-warehouse/</guid><description>Before signing a lease on more square meters, simulate. System dynamics routinely finds double-digit headroom in the operation you already have — and, if you do move, the location that minimizes cost.</description><pubDate>Sat, 04 Jul 2026 00:00:00 GMT</pubDate><category>system-dynamics</category><category>operations</category><category>logistics</category></item><item><title>Top AI Consulting Firms for Operations (2026 Guide)</title><link>https://antenor.ai/blog/top-ai-consulting-firms-operations-2026/</link><guid isPermaLink="true">https://antenor.ai/blog/top-ai-consulting-firms-operations-2026/</guid><description>An honest comparison of six AI consulting firms for operations work in 2026: Antenor, Tryolabs, RTS Labs, Prolego, Width.ai and Neurons Lab, and who fits what.</description><pubDate>Sat, 04 Jul 2026 00:00:00 GMT</pubDate><category>ai-consulting</category><category>operations</category><category>guide</category></item><item><title>The Automation Worth Building Is the One That&apos;s Impossible by Hand</title><link>https://antenor.ai/blog/automation-that-was-impossible-by-hand/</link><guid isPermaLink="true">https://antenor.ai/blog/automation-that-was-impossible-by-hand/</guid><description>Most automation shaves minutes off work a person could still do. The automation that pays does what a person fundamentally cannot — like rating and settling thousands of clients&apos; calls against a tariff in two hours, a run that was impossible manually.</description><pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate><category>process-automation</category><category>operations</category><category>ai-agents</category></item><item><title>You Can Count Crops From Space — Accurately Enough to Trust</title><link>https://antenor.ai/blog/counting-crops-from-space/</link><guid isPermaLink="true">https://antenor.ai/blog/counting-crops-from-space/</guid><description>Open satellite imagery plus machine learning turns &apos;how much land is planted&apos; into a measured number. Validated against a government&apos;s own sown-area figures, our classifier reached over 90% accuracy — no proprietary data required.</description><pubDate>Thu, 02 Jul 2026 00:00:00 GMT</pubDate><category>computer-vision</category><category>remote-sensing</category><category>predictive-models</category></item><item><title>When Your Data Is Too Big for a Normal Database</title><link>https://antenor.ai/blog/when-your-data-is-too-big-for-a-database/</link><guid isPermaLink="true">https://antenor.ai/blog/when-your-data-is-too-big-for-a-database/</guid><description>At carrier scale — hundreds of billions of records, ingested continuously, queried in under a second — a general-purpose database can&apos;t hold both ends of the trade-off. You stop fighting the tool and engineer for the workload&apos;s real shape.</description><pubDate>Wed, 01 Jul 2026 00:00:00 GMT</pubDate><category>custom-software</category><category>data-engineering</category><category>search</category></item><item><title>How to Tell If a Machine Learning Model Actually Works</title><link>https://antenor.ai/blog/how-to-tell-if-a-model-actually-works/</link><guid isPermaLink="true">https://antenor.ai/blog/how-to-tell-if-a-model-actually-works/</guid><description>Most models look brilliant right up to the first live decision. The difference between a result and an anecdote is the validation discipline: strict temporal separation, genuinely unseen data, and explicit defenses against the ways you fool yourself.</description><pubDate>Tue, 30 Jun 2026 00:00:00 GMT</pubDate><category>predictive-models</category><category>machine-learning</category><category>evaluation</category></item><item><title>Why Most AI Initiatives Stall Before Production</title><link>https://antenor.ai/blog/why-ai-initiatives-stall/</link><guid isPermaLink="true">https://antenor.ai/blog/why-ai-initiatives-stall/</guid><description>The six failure modes that keep AI projects in pilot purgatory, how to detect each one early, and the single habit that separates shipped systems from demos.</description><pubDate>Tue, 30 Jun 2026 00:00:00 GMT</pubDate><category>ai-strategy</category><category>mlops</category><category>consulting</category></item><item><title>Process Automation: Build vs Buy in 2026</title><link>https://antenor.ai/blog/process-automation-build-vs-buy/</link><guid isPermaLink="true">https://antenor.ai/blog/process-automation-build-vs-buy/</guid><description>A decision framework for AI process automation: when off-the-shelf tools win, when custom is cheaper over three years, and the integration test that settles it.</description><pubDate>Fri, 26 Jun 2026 00:00:00 GMT</pubDate><category>process-automation</category><category>ai-agents</category><category>strategy</category></item><item><title>Weather Nowcasting with Public Data: What We Learned</title><link>https://antenor.ai/blog/weather-nowcasting-public-data/</link><guid isPermaLink="true">https://antenor.ai/blog/weather-nowcasting-public-data/</guid><description>Lessons from building a convective nowcasting system on SINARAME radar and GOES-19 satellite data: pipelines, baselines, verification, and honest skill claims.</description><pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate><category>nowcasting</category><category>forecasting</category><category>machine-learning</category></item><item><title>The ROI Math of Predictive Maintenance with Machine Learning</title><link>https://antenor.ai/blog/predictive-maintenance-roi/</link><guid isPermaLink="true">https://antenor.ai/blog/predictive-maintenance-roi/</guid><description>A cost model for predictive maintenance: the four value drivers, the full cost side including false alarms, and a break-even test to run before building anything.</description><pubDate>Thu, 18 Jun 2026 00:00:00 GMT</pubDate><category>predictive-maintenance</category><category>machine-learning</category><category>roi</category></item><item><title>Route Optimization at Scale: Solving TSP for Last-Mile Logistics</title><link>https://antenor.ai/blog/route-optimization-tsp-logistics/</link><guid isPermaLink="true">https://antenor.ai/blog/route-optimization-tsp-logistics/</guid><description>Why last-mile routing is not textbook TSP, which solver strategies survive real dispatch operations, and what it takes to serve optimized routes in seconds via API.</description><pubDate>Sun, 14 Jun 2026 00:00:00 GMT</pubDate><category>route-optimization</category><category>logistics</category><category>operations-research</category></item><item><title>RAG vs GraphRAG: When Knowledge Graphs Actually Pay Off</title><link>https://antenor.ai/blog/rag-vs-graphrag/</link><guid isPermaLink="true">https://antenor.ai/blog/rag-vs-graphrag/</guid><description>What GraphRAG adds over vector RAG, what graph construction really costs, and the query patterns where a knowledge graph earns its keep in production.</description><pubDate>Wed, 10 Jun 2026 00:00:00 GMT</pubDate><category>rag</category><category>graphrag</category><category>knowledge-systems</category></item></channel></rss>