Security & Privacy
Protect sensitive information with access controls, encryption, and configurable data handling policies.
AI infrastructure
for the software you
Purpose-built software, connected models, and cloud systems.
Designed and engineered as one.
ENTERPRISE AICapitalize on AI
Capitalize on AI
across your enterprise.
Connect AI to your people, systems, and workflows to improve productivity, accelerate decisions, and deliver measurable business value.
How it works · request path
Deploys to your cloud, a private environment, or a managed platformRequests
Controls
Security & Policy Controls
Orchestration
AI Orchestration
Outcomes
Enterprise data
DetailHover over or select any part of the diagram to see its role.
- 01
Authorize
Verify identity and enforce access permissions.
- 02
Protect
Apply data masking and security policies.
- 03
Orchestrate
Route requests to the appropriate models and tools.
- 04
Audit
Capture activity for traceability and review.
Performance
Match models and infrastructure to your workloads for responsive, reliable AI experiences.
Business Value
Prioritize use cases tied to measurable improvements in productivity, quality, and service.
Governance
Define permissions, approval workflows, and audit trails for accountable AI adoption.
Integration
Connect AI with your existing business systems, knowledge sources, and workflows.
Cost Control
Track usage and spending by team and use case, with budgets, limits, and model routing.
AI infrastructureBuilt for the model.
Built for the model.
Ready for the workload.
Compute, inference, data access, and runtime. Designed as one system, so the software you build has a place to run.
- 01
Compute
Silicon and capacity sized to the model, not a generic cluster.
- 02
Inference
Model access, routing, and limits shaped around the task.
- 03
Data access
Permissioned context. The model sees what the workflow allows.
- 04
Runtime
Deployment, observation, and the environment the system runs in.
Built around your workloadOne foundation.
One foundation.
Every layer.
We build the software and the AI infrastructure behind it. Models, business data, interfaces, and cloud architecture—connected around the work your system needs to do.
ModelsIntegration & inference
DataContext & permissions
CloudDeployment & operation
system / architecture
01
applicationBusiness logic & interfaces02
model layerIntegration & inference03
data connectionsContext & permissions04
cloud runtimeDeployment & monitoring One connected architecture.
Illustrative system outline
3
Connected capabilities
7
Selected client projects
12
Education learning paths
Selected work
Brand and e-commerce
Unionaire
Product discovery, online shopping, and customer support.
Explore website
Business services
Fine Stone
Installment requests, customer support, and contact services.
Explore website
Aluminum systems
Smart System
Entrances, windows, and facades, built with thermal-break aluminum.
Explore websiteAI on the cloud you chooseVertex AI. SageMaker. Bedrock.
Vertex AI. SageMaker. Bedrock.
Engineered as one system.
Training, fine-tuning, and inference on managed AI platforms and the GPU infrastructure behind them. The same architecture, whichever cloud runs it.
Google CloudProduction
Vertex AI
Gemini and open models, trained, tuned, and served inside your Google Cloud project.
- Model Garden & GeminiModels
- Pipelines & custom trainingTrain
- Online & batch predictionServe
- GKE with GPUs & TPUsCompute
Amazon Web ServicesProduction
SageMaker & Bedrock
Foundation models and your own, on managed endpoints with AWS-native access control.
- Bedrock foundation modelsModels
- SageMaker training & HyperPodTrain
- Real-time & serverless endpointsServe
- EKS with GPU nodesCompute
Microsoft AzureProduction
Azure AI Foundry
OpenAI and open models with enterprise identity, private networking, and managed endpoints.
- Azure OpenAI & model catalogModels
- Azure ML training jobsTrain
- Managed online endpointsServe
- AKS GPU node poolsCompute
Self-hosted & hybridPrivate
Your GPUs. Your boundary.
Open models on Kubernetes or dedicated GPU servers when data residency, cost, or latency rules out a managed platform.
- vLLM & NVIDIA TritonServe
- Kubernetes GPU schedulingCompute
- Private networking & VPNAccess
- Autoscaling & cost controlOperate
- Vector search & RAGData
- Monitoring & evaluationObserve
- DataPermissioned sources and pipelines.
- TrainFine-tune or adapt the model.
- EvaluateMeasure quality before release.
- DeployEndpoints sized to the workload.
- ObserveLatency, cost, and drift in view.
Choose how to get started
Build a new system
Turn a complex workflow into purpose-built software with AI at its core.
- Workflow and requirements discovery
- Application and AI architecture
- Model and data integration
- Cloud deployment planning
Connect what you have
Bring AI into the applications, data, and infrastructure your team already uses.
- Existing systems and API review
- Data access and permissions
- Integration and inference design
- Monitoring and operational handover