Hosted inference

Your API key.
Our Nairobi GPUs.
Your data stays.

Production LLM endpoints without a six-month hardware procurement cycle, sovereign hosting with uptime commitments and logs your security team owns.

Scoped
SLA in the contract
NBI
Primary region
OpenAI
Compatible API
No CapEx
Opex model

Your CTO wants AI in production this quarter. Procurement wants three vendor quotes for GPUs that won’t ship until next year. Managed sovereign AI is the middle path: a private LLM API in Nairobi, metered like cloud, governed like on-prem.

Point your apps, RAG pipelines, and internal tools at a Kenya endpoint. Same integration patterns as foreign APIs, different physics for KDPA, board questions, and “where did that prompt go?”

What you get

A dedicated tenant, free of shared-GPU bingo.

Chat & completion API

OpenAI-compatible endpoints for apps, agents, and batch jobs, rate limits per tenant.

Embeddings

Local vector generation for RAG, pairs with private chat and policy desks.

Observability

Latency, token usage, error rates, dashboards your SRE team can wire into existing tools.

Model lifecycle

Security patches, version upgrades, rollback paths, we operate; you consume.

$ curl https://YOUR-KENYA-ENDPOINT/v1/chat/completions \
 -H "Authorization: Bearer sk-tenant-bank-***" \
 -d '{"model":"llama-70b-ke","messages":[...]}'

ROUTE tenant: your-org · example route
HOST Kenya GPU (example host)
LATENCY measured on your traffic, your own traffic, free of a fake p95
LOG retention 90d · DPO exportable
✓ Kenya-hosted inference on this path

When managed beats owned

CapEx math for Kenyan enterprises.

01
Pilot phase
Prove use cases before GPU racks hit the data-centre floor plan.
02
Burst workloads
Month-end document batches, audit seasons, scale without idle hardware.
03
Regulated tenants
Dedicated capacity tiers when noisy neighbours aren’t acceptable.
04
Migration path
Graduate to on-prem deployment when volume justifies owned silicon.
A common path we scope: start on a managed Nairobi API, then move inference to owned GPUs if load and data class justify the hardware. Same API shape, different bill. That is a pattern, a pattern, with no client name attached.

Combine with AI gateway to block staff from bypassing your endpoint, and model routing when you need task-specific model selection.

FAQ

Procurement and architecture.

How is this different from Azure OpenAI?

Geography and control. Inference runs on Kenya-hosted infrastructure under contract terms you negotiate, off a foreign region picked in a portal dropdown.

What models are available?

Curated open-weight stacks (Llama, Mistral, Qwen families) plus embedding and reranker endpoints. We advise on fit; you don’t babysit CUDA drivers.

Can we migrate to on-prem later?

Yes. Same API shapes make lift-and-shift to your cluster a planned migration, short of a rewrite.

Who sees our prompts?

Your tenant logs. Corvux ops access is break-glass only, documented, and auditable, outside “support might peek.”

Get a tenant on Nairobi GPUs

Share expected token volume and latency needs. We return SLA terms and a pilot endpoint in days, well short of quarters.

Request managed AI pricing