Application companies are vertically integrating to own their intelligence layer — driven by cost pressure at scale, latency needs, domain-specific performance gains from open models, and p…

For companies with zero or negative margins on AI features, sovereign AI is a must-have not a nice-to-have. The more successful the AI product, the higher the API costs, creating a paradox…

The build-vs-buy decision for AI capabilities hinges on four factors: COGS impact, latency sensitivity, whether domain fine-tuning beats closed models, and data proprietary-ness — with the…

New open weight models from Moonshot AI (Kimi K3) and Zhipu AI (GLM) now provide baselines close to closed-model frontier, making it feasible for companies to achieve better-than-frontier p…

New open-weight models from Moonshot AI and Zhipu AI have achieved near-frontier performance while providing full weight access, making them superior starting points for custom post-trainin…

Building sovereign AI demands a complex infrastructure stack: a production harness on top of a custom model, plus a development stack for evals, high-quality post-training data (expert traj…

Owning intelligence transforms the stack from simple API calls to a complex production harness (model + context + tools) plus a development stack (evals, data, RL environments, online learn…