Cloud consulting services for AWS, Azure and Google Cloud.

We design cloud-native architectures on AWS, Azure and Google Cloud that balance scalability, security and cost, then move your workloads there without stalling halfway.

What we deliver

• Multi-account and multi-subscription landing zones with governance guardrails
• Well-Architected and Cloud Adoption Framework reference architectures
• Data-center and VMware to cloud migration, including monolith-to-microservices modernization
• Hub-and-spoke networking, ExpressRoute, VPN, private connectivity and DNS
• Zero Trust identity with IAM, Entra ID, SAML/OIDC and encryption by default
• High availability, disaster recovery and multi-region design

Built for regulated industries

Architectures align with SOC 2, ISO 27001, HIPAA, FedRAMP and NIST so compliance is designed in rather than bolted on.

We build internal platforms and golden paths that engineering teams adopt on their own, which is how our founder’s work at a large bank produced about 30% faster deployments.

Infrastructure as Code

• Terraform modules for multi-cloud, Azure Bicep and ARM templates, AWS CloudFormation
• Ansible for configuration management and legacy deployment automation
• Drift detection, policy as code and reusable module libraries

CI/CD and GitOps

• Pipelines on GitHub Actions, GitLab CI/CD, Azure DevOps and Jenkins
• Kubernetes on EKS, AKS and GKE with ArgoCD, canary and blue/green releases
• Shift-left DevSecOps: vulnerability scans and compliance checks in every pipeline

As a Datadog Partner, we give you one view across infrastructure, applications, logs and security, then use that data to take waste out of your cloud bill.

Monitoring and observability

• Datadog agent rollout, APM and distributed tracing, infrastructure and log monitoring
• Custom dashboards, SLOs, anomaly detection and alert tuning
• OpenTelemetry instrumentation, Prometheus and Grafana, Dynatrace and Splunk
• Integration with CI/CD, Kubernetes, Terraform and ITSM tools

Cloud cost optimization (FinOps)

• Tagging enforced by policy and cost attribution per business unit
• Rightsizing, scheduling and commitment planning across AWS, Azure and GCP
• Cost checks inside CI/CD so engineers see the price of a change before it merges

Across past engagements this approach has averaged about a 33% reduction in annual cloud spend.

We apply AI to cloud and IT operations with the identity, approval and cost controls production systems need.

• Event correlation that opens only real incidents at the right severity
• Outage prediction and prevention using Datadog and telemetry insights
• Agent workflows using MCP, A2A and LangGraph, with human approval for high-risk actions
• Governed AI platforms on Amazon Bedrock, Azure AI Foundry and Vertex AI
• AI-assisted Terraform and pipeline development
• Per-tenant token and GPU cost tracking