<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Discovery AI Resources</title><description>Guides for the teams that own the matter, in-house and at the firm: the economics of bringing document review in-house, what defensible AI review means, and how Discovery AI runs in your own Azure.</description><link>https://www.discoveryai.io/</link><item><title>Azure AI Foundry (now Microsoft Foundry) for legal teams: a CIO&apos;s primer</title><link>https://www.discoveryai.io/resources/azure-ai-foundry-for-legal-teams/</link><guid isPermaLink="true">https://www.discoveryai.io/resources/azure-ai-foundry-for-legal-teams/</guid><description>Microsoft Foundry, formerly Azure AI Foundry, is Microsoft&apos;s platform for running AI models inside an Azure subscription. When a legal AI platform deploys in your own tenant, your documents, models and sign-in stay under your existing governance, your data stays out of model training, and Microsoft bills the usage at list price.</description><pubDate>Fri, 09 Oct 2026 00:00:00 GMT</pubDate></item><item><title>Per-GB vs. per-matter pricing: a CFO-friendly comparison</title><link>https://www.discoveryai.io/resources/per-gb-vs-per-matter-pricing/</link><guid isPermaLink="true">https://www.discoveryai.io/resources/per-gb-vs-per-matter-pricing/</guid><description>Per-gigabyte eDiscovery pricing ties your bill to data volume you can&apos;t know until processing is done, and hosting fees keep running for the life of the matter. Per-matter pricing sets the price by the complexity of the matter before work starts. For budgeting, per-matter is the more predictable model.</description><pubDate>Fri, 02 Oct 2026 00:00:00 GMT</pubDate></item><item><title>What &quot;defensible AI review&quot; actually means in practice</title><link>https://www.discoveryai.io/resources/defensible-ai-review/</link><guid isPermaLink="true">https://www.discoveryai.io/resources/defensible-ai-review/</guid><description>Defensible AI review means you can explain and support every review decision if opposing counsel, a court, or a regulator asks. In practice that takes a written reason for each call cited to the source document, a log of every agent and reviewer action, human sign-off where stakes are high, and quality checks you can describe.</description><pubDate>Fri, 25 Sep 2026 00:00:00 GMT</pubDate></item><item><title>The economics of bringing litigation document review in-house</title><link>https://www.discoveryai.io/resources/economics-of-bringing-litigation-review-in-house/</link><guid isPermaLink="true">https://www.discoveryai.io/resources/economics-of-bringing-litigation-review-in-house/</guid><description>First-level document review is the most expensive phase of most matters, and the one legal teams send out most often. Bringing it in-house on an agentic review platform cuts the cost of a representative matter by roughly half, runs about 20× faster than manual or TAR review, and leaves a defensible record your team owns.</description><pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate></item></channel></rss>