Infrastructure and Production services
The many different platforms and new uses our new-found mobility has fostered have resulted in various different challenges related to IT infrastructure, such as high availability, virtualisation and infrastructure security.
This division is dedicated to Infrastructure and Production, and works on clients’ projects to tackle issues surrounding on-demand resource availability, flexibility, ease of access and self-service access. Setting up a public, private or hybrid cloud, for example, requires clients to overhaul their entire security system, within a virtual, shared environment and featuring IT components that are increasingly network-focused.
Infrastructure, Production & Generative AI Offering
The rapid evolution of digital usage—mobility, virtualization, hybrid cloud, and the explosion of data—now requires a new generation of infrastructures: scalable, intelligent, automated, and capable of supporting advanced AI workloads, including model training, AI agent deployment, and orchestration of complex data pipelines.
Our “Infrastructure, Production & AI” practice supports organizations in transforming their IT environments toward these next-generation models, natively integrating high availability, security, automation, AIOps, MLOps, and GPU/HPC capabilities.
We operate across the entire lifecycle of cloud, data, and AI environments: design, implementation, automation, intelligent monitoring, security, optimization, and operations.
Our Areas of Expertise
Modernizing and Automating Infrastructures
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Cloud-native architectures (Public, Private, Hybrid, Edge)
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Resilient, scalable, microservices-oriented platforms
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Advanced automation (IaC, CI/CD, GitOps, AIOps)
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Virtualization and containerization optimized for AI workloads
Accelerate AI & Agentic Use Cases
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Deployment of GPU / HPC / TPU infrastructures
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Implementation of clusters optimized for model training (LLMs, computer vision, AI agents)
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Management of MLOps pipelines (training, fine-tuning, evaluation, monitoring, governance)
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Deployment and orchestration of AI agents (specialized agents, multi-role agents, autonomous workflows)
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Integration of AIOps for anomaly detection, incident prediction, and automated remediation
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AI cost optimization and intelligent resource tuning
Ensuring Security & Compliance
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Securing cloud, data, and AI environments
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Protection of models, training data, and pipelines
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Implementation of Zero Trust, IAM, PAM, SIEM, and AI-enhanced XDR
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Behavioral analysis and threat detection using ML models
Our Key Capabilities
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Design and operation of AI-ready environments
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On-demand access to resources (CPU, GPU, high-throughput storage)
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Intelligent workload scheduling (GPU/CPU optimization)
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AI-driven predictive capacity planning
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AI-enhanced monitoring (AIOps, NLP Ops, log intelligence)
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Architecture audits, optimization, and redesign
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End-to-end automation (CI/CD, GitOps, MLOps, AgentOps)
Our Technology Expertise
🌐 Cloud & AI
Azure, AWS, Google Cloud
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Native AI services (Azure AI, Bedrock, Vertex AI)
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Distributed AI architectures, hosted models, RAG, vector databases
⚙️ GPU, HPC & Model Training
NVIDIA DGX, CUDA, TensorRT
Kubernetes with GPU, Kubeflow, Airflow
Databricks, MLflow, Ray, Hugging Face
🧩 Automation, DevOps, MLOps & AgentOps
Python, PowerShell
Terraform, Ansible, Puppet
Kubernetes, Docker, OpenShift
Jenkins, GitHub Actions, GitLab CI
LangChain, OpenAI Ops, crewAI, AutoGen
📊 Big Data & Streaming
Hadoop, Spark, Kafka
Elasticsearch, Logstash, Kibana
🔒 Security & Networking
Cisco ACI, SD-WAN
F5, Firewalls, Zero Trust
SIEM: Splunk, Elastic SIEM, Sentinel
IAM / PAM: CyberArk
🧭 Digital Workplace & Mobility
Microsoft 365, Intune
Intelligent environments integrating copilots and agents
OBJECTIVE: Provide organizations with a modern, automated, secure, and optimized infrastructure capable of supporting current and future needs: Cloud, Data, Generative AI, LLM training, agent-based systems, and intelligent operations.