01AI-native consultancy

AI-native consultancy. Built for sovereignty.

We design and deliver personalized AI products — strategy through implementation, in one engagement, on infrastructure you own. Custom systems for your stack, your servers, your weights.

Headquartered
Nairobi, Kenya
Markets
5 countries
Deployed on
Your infrastructure
An outer public cloud silhouette is shown disconnected from a customer's infrastructure boundary, inside which six AI components — private LLM, document intelligence, conversational BI, evals, observability, and governance — are interconnected.PUBLIC CLOUDYOUR INFRASTRUCTURENO EGRESSLLMDOC INTELBIEVALOBSERVABILITYGOVERNANCE

The differentiator

Ownership is not a feature. It's the architecture.

Every other AI vendor sells you access. We deliver systems you keep when we leave.

Your stack.

Every system we build slots into your existing tech: your warehouse, your auth, your observability, your ticketing.

Your servers.

We deploy on your AWS, Azure, GCP, or on-premise infrastructure. Prompts and data never leave your perimeter.

Your weights.

Code, model weights, training pipelines, and runbooks are yours forever. There is no platform, no SaaS, no lock-in.

Your product.

We don't sell a product — we design and deliver yours. Every engagement is shaped to your business, not a configured template.

Built by

Senior AI engineers, not a body shop.

Kevin Mburu

Kevin Mburu

Founder & CEO

Founder & CEO of Ubuntu Online. Leads strategy and delivery for AI consultancy work — building custom AI systems that customers actually own — code, weights, training pipelines, and runbooks — on infrastructure they control.

Rudresh Narwal

Rudresh Narwal

Head of Engineering

Leads engineering for Ubuntu Online. Builds production-grade enterprise AI and automation workflows, scaling private LLM platforms from POC to production. Full-stack background spanning fintech, insurance, and AI infrastructure.

Ravi Piplani

Ravi Piplani

Strategic AI Head

Heads strategic AI for Ubuntu Online. Builds enterprise operating systems powered by AI and owns the architecture, model selection, and engagement model that turn AI initiatives into production systems leadership actually trusts.

Gulshan Y.

Gulshan Y.

AI Researcher

AI researcher focused on model evaluation, fine-tuning, and the eval pipelines that keep private LLM deployments accurate as base models evolve. Works across model selection, retrieval, and post-training methods.

Strategy + Implementation · One engagement · No handoffs

The Ubuntu Method.

Most consultancies hand strategy to one team and implementation to another, and the client pays for the seam. We deliver both — same engineers, same engagement, four phases.

The Ubuntu Method: a four-phase engagement from Discover to Operate.01Discover2–3 wk02Strategize1–2 wk03Build4–8 wk04Operate1–2 wk

What we ship

Reference architectures, not slideware.

We deliver under NDA. Below is the shape of a private LLM deployment, drawn the way we actually build it. The highlighted path traces inference data: request, model, observability, sink.

A bounded VPC contains nine components arranged top-to-bottom: Identity Provider, Auth Proxy, and API Gateway in the authentication row; vLLM Cluster, Doc Pipeline, Conv BI, and Eval Runner in the services row; Observability collects from all services; Data Warehouse sits at the bottom as the final sink. The highlighted clay path traces Auth Proxy through the API Gateway, into the vLLM Cluster, down to Observability, and into the Data Warehouse.YOUR VPC · YOUR CONTROLINFERENCE PATHIdentity ProviderOKTA · ENTRA · ADAuth ProxyOAUTH2 · OIDCAPI GatewayRATE LIMITING · WAFvLLM ClusterGPU POOLDoc PipelineQUEUE · WORKERSConversational BINL → SQLEval RunnerCI · GOLDEN SETSObservabilityPROM · LOKI · GRAFANAData WarehouseSNOWFLAKE · BQ · POSTGRESDATA FLOWSUPPORTING SERVICES

What this shipped

50K+
Docs / dayTier-1 East African bank
8 wk
Build timeInitial production deploy
99.7%
Extraction accuracyOn 200K-page gold set
0
Bytes egressedAcross 100% of deployments
See more reference architecturesNamed references on strategy call

The obvious question

Why not just build it ourselves?

You can. Here is what changes when you don't.

Build it yourselfDIY PATH
Ubuntu OnlineSOVEREIGN PATH
TIME TO PRODUCTION

9–18 months

MLOps stack, eval suite, governance layer — built from scratch by engineers also doing their day jobs.

6–12 weeks

Open-source models, vLLM, and modern eval tooling — assembled, integrated, deployed, and operated on your infra.

QUALITY FLOOR

Hallucinations in prod

Most teams rush to a model and ship without an eval suite. Production hallucinations kill the project.

Eval pipeline first

We build the eval pipeline before the first model goes live, and the governance layer before the second model arrives.

OPERATE

Heroic engineer

When the original team rolls off, the system depends on one or two people who remember how it works.

Your whole team

We hand over with documentation, runbooks, training, and an optional support engagement. Your team runs it.

Common questions

Frequently asked questions

What does Ubuntu Online do?
Ubuntu Online is an AI-native consultancy that designs and builds custom AI systems deployed on the customer's own infrastructure. The customer owns the code, the model weights, and the data.
Where do you operate?
Headquartered in Nairobi, Kenya. Engagements across Africa (Kenya, Nigeria, South Africa, Tanzania, Uganda, Rwanda), Canada, the United States, and India.
Do you build SaaS or custom?
Custom. Every system is built into your existing stack and runs on your own infrastructure. We are not a SaaS vendor.
Can you train a private LLM on our data?
Yes. Fine-tuning of open-source models and from-scratch small language model training are core capabilities. We deploy on your cloud or on-premise environment, and you own the weights.
How do engagements start?
Book a 30-minute strategy call. We talk through your tech stack, your data, and the specific AI opportunity. No commitment to scope on the first call.

The closer

Build the AI you'd be proud to own.

Thirty minutes to talk through your stack, your data, and the AI opportunity you care about most. No pitch deck. No sales theatre.

Ubuntu Online · Nairobi · 2026
Book a strategy call