Manual configuration
Console changes leave environments inconsistent and make infrastructure hard to reproduce.
Cloud Architecture
Build your cloud. Put AI to work.
We design and modernize AWS and Google Cloud infrastructure for your applications, data, and AI. Then we help your team use AI to build and operate it.
AWS
Google Cloud
AI-assisted operations
The problem
Cloud complexity grows faster than the team.
Ad hoc infrastructure gets harder to change as workloads grow. Adding AI brings new demands on data access, compute, and budgets.
Fragile workloads
Applications outgrow their original design. Scaling, backups, and recovery need a deliberate plan.
Rising cloud bills
Idle resources, oversized compute, and AI usage add up without clear budgets or owners.
What we build
Infrastructure that fits your workloads.
Whether you are moving to AWS or Google Cloud, or improving an existing environment, we start with your applications, data, and operating requirements.
Cloud foundations
Structure accounts or projects, network boundaries, identity, and access. Define environments in infrastructure as code so your team can review and reproduce them.
Application and data architecture
Choose managed services, containers, serverless, or virtual machines to match the workload. Plan storage, databases, and data flows around performance and growth.
AI workloads in production
Connect models to the data and services they need. Design for access controls, response times, usage limits, and compute capacity as adoption grows.
Reliability and cost
Build in monitoring, backups, and tested recovery. Track spend by workload, set budgets, and give your team clear responsibility for day-to-day operations.
Applications
Data pipelines
AI workloads
AWS or Google Cloud
Compute
Networking
Identity
Storage
Monitoring
AI for cloud operations
Use AI to improve how your cloud runs.
Give AI the context of your infrastructure, telemetry, and operating procedures so it can help engineers make informed changes.
Plan infrastructure changes
Use AI to draft infrastructure code, explain proposed changes, and check configurations against your team's standards.
Investigate incidents
Bring logs, metrics, and recent deployments together so AI can help narrow likely causes and suggest the next checks.
Find avoidable spend
Use AI to analyze usage and billing patterns, flag idle resources, and suggest capacity changes for engineers to validate.
Engineers review proposed changes. Approved automation runs within defined permissions, with an audit trail and a rollback path.