Privately held domain
client.ai is for sale
I bought client.ai as a brand for a startup idea. I’d like to sell at fair market price to someone who can make better use. Buy it now for US $795,000. Or make an offer. Direct message Mark on LinkedIn to inquire — DMs are open.
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PC manufacturers shipped more than 270 million computers in 2025. Investment in local inference includes EnCharge AI’s $100M-plus Series B for accelerators targeting personal computers. On the software side, Windows ML runs models locally across CPUs, GPUs, and NPUs, giving applications access to on-device AI through a shared runtime.
PC Market
Worldwide PC shipments exceeded 270 million in 2025, growing 9.1%
Gartner: 2025 PC shipment results
AI Silicon
EnCharge AI raised more than $100 million to commercialize local AI accelerators
EnCharge AI: $100M-plus Series B
Local Inference
Windows ML runs AI models on CPUs, GPUs, and NPUs through one framework
Microsoft: Windows ML overview
PC Market
Worldwide PC shipments exceeded 270 million in 2025, growing 9.1%
Gartner’s preliminary full-year results put worldwide PC shipments at 270.2 million in 2025, up 9.1% from 2024. This measures the whole PC market, including conventional and AI PCs.
Gartner identifies Windows 11 upgrades as a major driver and notes that vendors promoted AI PCs during the replacement cycle. Many organizations were buying for future capabilities rather than demonstrated productivity gains from local AI.
AI Silicon
EnCharge AI raised more than $100 million to commercialize local AI accelerators
In February 2025, EnCharge AI announced a Series B exceeding $100 million, led by Tiger Global. The company said the funding would advance its first accelerators focused on client computing and brought total funding above $144 million.
The announced architecture combines analog processing and memory to reduce inference power requirements on local devices. Participants included Samsung Ventures and RTX Ventures.
Local Inference
Windows ML runs AI models on CPUs, GPUs, and NPUs through one framework
Microsoft’s Windows ML framework supports local AI inference across CPUs, GPUs, and NPUs. Windows can install and update hardware-specific execution providers, reducing the need for applications to bundle separate vendor runtimes.
Models can execute without a network connection or a cloud inference call. Microsoft also supports sharing the runtime across applications; hardware acceleration availability depends on the device and Windows version.
Context for client.ai
PC shipments
EnCharge AI
analog computing
Windows ML
offline inference
Gartner estimates 270.2 million PCs shipped in 2025, up 9.1% year over year. The figure covers all PCs, not only devices marketed for AI.
The February 2025 Series B exceeded $100 million, bringing total funding above $144 million. EnCharge identified commercialization of its first client-computing accelerators as a use of the proceeds.
EnCharge combines analog processing and memory to reduce the power required for inference on local devices.
Windows ML is powered by ONNX Runtime. Applications can share a Windows-maintained runtime and obtain hardware-specific execution providers dynamically.
Windows ML supports running models on the user’s hardware without an internet connection. CPU, GPU, and NPU acceleration provide deployment options across supported devices.