Guides, research notes and what we learn building models.
A practical guide for CTOs and finance teams on how to allocate AI budgets across infrastructure, software, people, and compliance — with frameworks by company size and AI maturity.
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A capacity planning walkthrough for on-premise AI: sizing GPU, storage, network and power, with a sizing worksheet and six common planning mistakes.
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A practical decision framework for choosing between cloud, on-premise, and hybrid AI infrastructure. Includes a workload-based decision matrix, cost benchmarks, and architecture patterns for each deployment model.
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A structured self-assessment framework across 6 dimensions — data, infrastructure, team, compliance, use case, and organizational readiness — with a scoring rubric and specific next steps for each readiness level.
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Three approaches to deploying an internal AI assistant that replaces unauthorized ChatGPT usage: commercial on-prem platforms, open-source stacks, and fine-tuned domain-specific models. Covers requirements, economics, the UX trap, and why data preparation is the real moat.
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A five-stage practical guide to converting unstructured enterprise documents — PDFs, Word files, scanned forms — into clean JSONL training data for small language model fine-tuning.
Read the articleTokens per second and cost per million tokens for fine-tuned models on CPUs, GPUs and NPUs, plus a decision framework for infrastructure teams.
Read the articleCost math and accuracy benchmarks for fine-tuned small language models against the GPT-4 API on enterprise workloads, plus a decision framework.
Read the articleHow fine-tuning dramatically improves JSON output reliability in small models — from 60% valid JSON to 99%+ compliance, with practical techniques for structured output tasks.
Read the articleAn 8x L40S server starts around $81,000 and an 8x H100 cluster around $295,000. Compare VRAM, bandwidth, power and cost per GB before you buy.
Read the article40% of enterprises report cloud AI spending exceeds projections. This article breaks down the eight hidden costs that turn a $50K cloud AI budget into $120K+ of actual spend, with real numbers and math for each category.
Read the articleMicrosoft's Foundry Local runs AI models on local hardware with no cloud connection at runtime. What it does well, where it stops, what enterprises need.
Read the articleA phased, step-by-step guide for migrating AI workloads from cloud to on-premise infrastructure. Covers workload classification, infrastructure planning, data pipeline migration, and the common pitfalls that derail enterprise migrations.
Read the articleFour healthcare AI agent use cases, from clinical documentation to coding audit, the HIPAA requirements they trigger, and how to run them on-premise.
Read the articleAttorney-client privilege can be waived by sending documents to cloud AI services. This guide covers four on-premise AI agent use cases for law firms and legal departments, the privilege and ethics requirements, architecture, and ROI math.
Read the articleWork out when self-hosting beats cloud API spend: the four numbers behind an on-premise AI break-even point, and typical payback by workload type.
Read the articleA vertical guide for government and defense buyers evaluating on-premise AI infrastructure — covering FedRAMP, ITAR, NIST 800-171, classified network compatibility, air-gapped operations, and the data preparation challenge most vendors ignore.
Read the articleA step-by-step audit process to discover unauthorized AI tools in your organization. Covers network traffic analysis, browser extension audits, SaaS spend analysis, employee surveys, DLP reviews, and API key audits — with a 25-item checklist you can use immediately.
Read the article77% of employees paste company data into unsanctioned AI tools. The average cost of insider risks tied to shadow AI is $19.5M per organization — a 20% spike in two years. Here's what's being leaked, why it's happening, and the structural fix.
Read the articleA practical, immediately usable AI acceptable use policy template for healthcare, financial services, and other regulated organizations. Includes data classification tables, regulatory overlays, and enforcement frameworks.
Read the articleThe complete journey from 'employees are using ChatGPT with company data' to 'we have sanctioned, auditable, on-premise AI tools.' A phased playbook with timelines, resource estimates, and ROI calculations.
Read the articleHow enterprises use fine-tuned small language models to extract structured data from PDFs — construction BOQs, legal contracts, medical records, and financial statements — at a fraction of manual processing cost.
Read the articleWhy enterprises are shifting from large foundation models to fine-tuned small language models running on-premise. Cost, latency, data sovereignty, and the fine-tuning workflow that makes it work.
Read the articleA country-by-country reference guide to data residency requirements for AI training data, model weights, and cross-border transfers. Covers EU (GDPR + EU AI Act), US, UK, China, India, Saudi Arabia, UAE, Australia, Brazil, Canada, Japan, and South Korea — with enforcement dates and practical implications for enterprise AI deployment.
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