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On-premise AI vs cloud AI in Kenya.

Cloud AI wins on convenience. On-premise wins when the law, the board, or the customer says data cannot leave.

This page is for CTOs and compliance leads evaluating whether foreign cloud AI is acceptable for their risk profile. Corvux builds private infrastructure so sensitive inference stays in Kenya.

Need the legal framing? Read our KDPA AI compliance guide.

Dimension	Corvux / private	Cloud alternative
Data residency	Kenya by design	Usually outside Kenya
Latency	LAN / local region	International round-trips
Dependency	Your hardware + open models	Vendor uptime & pricing
Compliance evidence	Physical + logical control	Contractual assurances only
Best for	Regulated workloads	Public, non-sensitive tasks

Decision guide

When cloud AI is fine, and when the fit fails.

Cloud AI wins when workloads are non-sensitive and you want zero hardware ownership. On-premise wins when KDPA localisation, latency on LAN, and model ownership weigh more than convenience.

Many Kenyan enterprises end up hybrid: public tools for marketing copy, private endpoints for core operations. Corvux builds the private half.

Next reads: KDPA AI compliance, data residency, on-premise infrastructure, and request a deployment.

Practical checklist

Ask these before you renew a cloud AI contract.

Where does inference run?

Name the country of the GPU region. “Africa” and Kenya are different places.

What data classes are in prompts?

If customer, employee, patient, or citizen data appears, treat it as a KDPA conversation.

Can you fine-tune locally?

Open weights on your GPUs allow domain adaptation without exporting corpora.

What does an auditor see?

Logs, access control, and a residency statement beat marketing one-pagers.

Want a side-by-side for your stack?

We will map which workloads must stay private and which can stay in the cloud.

Book a comparison call