AI & Machine Learning
Production AI — without defaulting to hyperscaler GPU list prices
Azure OpenAI, custom ML and MLOps for Israeli teams — plus lower-cost GPU capacity when Azure and AWS list pricing does not fit. Real engineers. Tier-1 Microsoft CSP.
Production AI on Azure, from readiness to deployment
We start with an AI Readiness Assessment, not a sales pitch.
Our engineers evaluate your data, infrastructure and use cases, then recommend a high-ROI starting point — typically document processing, a support copilot or predictive analytics. From there we build, deploy and operate your Azure AI services in Israel with MLOps, monitoring and enterprise security baked in, so models stay reliable in production.
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GPU · AI compute
Azure and AWS GPU is expensive. There are alternatives.
You do not have to default to hyperscaler list prices for every AI workload. Cloudi brings the knowledge, the relationships, and lower-cost capacity — so you can run GPU where it makes sense, at a cost that fits the roadmap.
Knowledge
Engineers who size AI workloads for cost and performance — not just catalog SKUs.
Relationships
Access to additional capacity paths beyond public-cloud GPU list pricing.
Lower cost
Capacity-first options so GPU spend tracks the work, not the list price.
Our AI Services
Azure OpenAI Integration
Bring the latest GPT-4o, o-series reasoning models and DALL-E into your apps through Azure OpenAI in Israel — inside your own tenant, never on the public ChatGPT API. We handle the integration, prompt engineering and evaluation for chatbots, content generation, code assistance and document analysis. Your prompts and data stay private, compliant and regional, with Microsoft enterprise security throughout.
Learn MoreWhy AI with Cloudi?
Enterprise AI on Azure — plus GPU capacity alternatives when list pricing does not fit
Enterprise Security
Azure AI services provide enterprise-grade security, compliance, and data protection. Your data stays within your Azure tenant and is never used to train public models.
Rapid Innovation
Access frontier models — GPT-4o, o-series reasoning models and DALL-E — through Azure OpenAI and Azure AI Foundry. Go from idea to production faster with pre-built AI services and model catalogs.
GPU Without List-Price Lock-In
Scale AI on Azure when it fits — and use additional lower-cost GPU capacity when Azure or AWS list pricing does not. Same engineers. Capacity that matches the workload.
AI Use Cases
Real-world applications transforming businesses today
Customer Service
AI chatbots and virtual agents for 24/7 support
Document Processing
Automated extraction and analysis of business documents
Predictive Analytics
Forecast demand, detect anomalies, optimize operations
Content Generation
Marketing copy, reports, and creative content at scale
Semantic Search
Intelligent search across enterprise knowledge bases
Quality Inspection
Computer vision for manufacturing and logistics
Code Assistance
AI-powered development with GitHub Copilot
Personalization
Tailored recommendations and user experiences
Azure AI & GPU: common questions
Straight answers from the engineers who build and run these systems
What's the difference between Azure OpenAI and the public ChatGPT API?
Azure OpenAI runs GPT-4o, o-series and related models inside your Azure tenant with enterprise security, compliance and regional data residency. Your prompts and data are never used to train public models — a requirement for most Israeli enterprises and regulated workloads.
Can Cloudi build a custom AI assistant on our own data?
Yes. We build RAG-based copilots and assistants using Azure AI Foundry and Copilot Studio that ground answers in your enterprise knowledge — Teams, SharePoint, Dynamics or custom systems — with proper prompt engineering and evaluation.
Do you handle MLOps, or just initial models?
Both. We operationalize models with MLOps/GenAIOps: versioning, automated training pipelines via Azure DevOps and GitHub Actions, monitoring, and retraining — so models stay reliable in production, not just in a notebook.
How do you keep our data secure in AI workloads?
Data stays within your Azure tenant with encryption, access controls and compliance built in. For sensitive workloads we use confidential VMs and isolated GPU compute, and we apply responsible-AI evaluation throughout.
Are Azure and AWS the only options for GPU AI workloads?
No. Azure and AWS GPU list pricing is often expensive for training and inference at scale. Cloudi helps you use additional lower-cost capacity where it fits — alongside Azure when you need it — so you are not locked into hyperscaler list prices for every workload. Talk to an engineer about what your stack needs.
Where do most companies start with AI?
Usually an AI Readiness Assessment: we evaluate your data, infrastructure and use cases, then recommend a high-ROI starting point — commonly document processing, a support copilot, or predictive analytics — before scaling. Talk to our team to scope yours.
Try Cloudi for AI & GPU
Talk to an engineer about Azure OpenAI, MLOps, or lower-cost GPU capacity — not a sales script.
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