From experiments to production
Convert promising pilots into reliable operational systems.
Enterprise AI • Infrastructure • Integration
EXZAI helps organizations design, deploy and operate private AI, enterprise assistants, automation and GPU infrastructure — from Abidjan to the wider African market.
On-premises • Private cloud • Hybrid AI
Real-world AI requires data integration, infrastructure, access controls and people who can keep everything running. EXZAI brings these disciplines together.
Convert promising pilots into reliable operational systems.
Choose where models run and how data is handled.
Integrate assistants and workflows into everyday business operations.
A practical end-to-end approach to enterprise AI.
Private AI assistants, RAG knowledge platforms, automation and business system integration.
Explore SolutionsDGX systems, GPU workstations, servers, clusters, storage and AI deployment architecture.
Explore InfrastructureDedicated AI environments, managed inference and scalable deployment options.
Explore CloudMonitoring, security, optimization, support and operational continuity.
Explore Managed ServicesExecutive workshops, IT training and practical AI enablement.
Explore AcademyRun AI on your own servers, in a dedicated environment or in a carefully designed hybrid architecture. EXZAI helps you choose the right combination of model performance, governance, cost and operational control.
On-premises
For sensitive workloads, internal network access and customer-owned hardware. Security and data residency depend on configuration and controls.
Private cloud
Managed isolated infrastructure with less hardware for your team to operate. Hosting location and contractual terms are specified for each engagement.
Hybrid
Keep private data operations in your environment and use external compute or APIs where appropriate. Requires a data-flow map and review of cross-border considerations.
Edge & desktop
For developer teams, local prototyping and disconnected or edge needs. Capacity depends on the chosen machine and model.
Ask questions across approved documents and retrieve cited answers.
Reduce repetitive work with controlled tools and human approvals.
Give teams faster access to relevant policies, procedures and information.
Extract, classify and organize information from business documents.
Connect model capabilities to authorised business applications.
Build interfaces and services shaped around your workflow.
Turn internal policies, manuals and technical documentation into a searchable AI workspace, with source references and permission-aware design.
Give employees access to an AI assistant on infrastructure aligned with your security, governance and data-handling requirements.
Move from a GPU workstation or DGX Spark development environment to a managed production inference service with monitoring and support.
EXZAI Infrastructure
From compact development systems such as NVIDIA DGX Spark to GPU servers and larger AI architectures, EXZAI helps specify and integrate the infrastructure your workloads actually need.
Compact development system for local AI workflows and experimentation.
Learn moreLarger deskside AI capacity for shared team workloads.
Shared platforms for enterprise inference and model development.
Learn moreScaled compute with high-speed networking, scheduling and storage.
Product specifications, commercial availability and configurations subject to confirmation.
Design use cases around the people, data and operating conditions of your sector.
We prioritize measurable use cases, a clear technical architecture, responsible deployment and long-term maintainability.
Business outcomes, data landscape, constraints and target users.
Architecture, model selection, security approach, total cost and pilot metrics.
A narrow proof of value measured against agreed evaluation criteria.
Production infrastructure, integrations, access, tests and documentation.
Monitoring, updates, support and optimization.
Administrator training, user adoption and ongoing improvement.
Yes, depending on your use case. EXZAI can design on-premises, private or controlled hybrid deployments. We document where data is processed and which components have external access.
Local AI runs models on hardware you control, on your premises or in a dedicated environment. Cloud AI relies on a provider's shared infrastructure or APIs. The right choice depends on data sensitivity, workload, budget and the operational effort you want to take on.
Often, yes. We review the available APIs, access permissions and business processes to design integrations appropriate to your environment.
Not necessarily. We assess whether you need dedicated on-premises compute, a hosted environment or a hybrid setup based on workload, privacy and budget.
Yes. Projects typically begin with a discovery discussion, a feasibility assessment and a scoped proposal, and can start with a pilot measured against agreed criteria before full deployment.
EXZAI plans ongoing administration, monitoring, security, optimization and training under a separately defined scope and support agreement.
Retrieval-augmented generation allows an AI application to retrieve relevant information from an approved knowledge source before generating an answer. It needs careful permissions, quality evaluation and monitoring.
Tell us what you want to build. We will help define a practical technical and commercial path.