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Market intelligence, buying guides, and AI trends for the people who choose technology.
The cloud was the only answer for a decade. Now the smartest teams are asking a sharper question, should some of it come back?
Everyone's reaching for the biggest AI model. The 1% are asking a sharper question: what's the smallest model that gets the job done?
Cloud bills were the last surprise. AI bills are the next one. Here's why AI costs behave differently, and how the 1% keep them in check.
Every AI agent you deploy gets logins, tokens, and access no one is tracking. Non-human identities are the security gap of 2026, here's how to close it.
One open standard is quietly rewiring how AI connects to software. Here's what MCP means for your stack, and the buying question it just added.
Many businesses assume their SaaS providers back up their data. They mostly don't. Here's how the shared responsibility model really works, what causes SaaS data loss, and how to protect the business-critical data living in your cloud applications.
Decoded by Sia7/31/202611 minEmployees now adopt SaaS and AI tools faster than any IT team can approve them. Here's what shadow IT really is, why it is both a genuine risk and a useful signal, what drives it, and how to gain visibility and govern it without grinding productivity to a halt.
Decoded by Sia7/31/202611 minSaaS spending grows quietly until it becomes one of the largest, least-governed line items in the business. Here's how to take control, discover every subscription, cut shelfware and redundancy, right-size licenses, and put purchasing under a repeatable process.
Decoded by Sia7/31/202612 minPublic, private, and hybrid cloud each solve a different problem. Here's a clear, side-by-side comparison of the three models across cost, security, control, and scalability, and a framework for placing each workload where it belongs.
Decoded by Sia7/31/202611 minThe open source versus proprietary debate is really a series of trade-offs around cost, control, security, and support. Here's an honest, side-by-side comparison of both models, where each wins, and a practical framework to choose the right one for each part of your stack.
Decoded by Sia7/31/202612 minMost enterprise AI projects stall on data, not models. Here's what AI-ready data actually means, why data readiness is the real bottleneck, the characteristics that separate usable data from raw data, and a practical path to building foundations that make AI reliable.
Decoded by Sia7/31/202612 minAs privacy laws spread and AI moves data across borders, where your data physically lives has become a legal and strategic question. Here's what data sovereignty, residency, and localization really mean, why they matter now, and how decision-makers should build a defensible data strategy.
Decoded by Sia7/31/202612 min