We connect product needs to cloud foundations, delivery workflows, runtime platforms, and AI systems.
Explore services- Foundation
- Accounts / projects
- Controls
- Security + cost
- Outcome
- Ready to scale
- Engagement
- Foundation build
Production-grade cloud. Battle-tested AI.
Build for scale
Resilient cloud foundations and scalable AI systems that help startups ship faster, control costs, and grow reliably.
Cloud
AI
Deploy
Observe
Scale
Positioning
Great AI features fail on brittle infrastructure. Massive cloud setups bleed money.
Xbase1 builds the intersection: cloud foundations and AI systems designed for real growth.
See how we work- AWS / GCP
- Cloud foundations
- Terraform
- Infrastructure as code
- CI/CD
- Delivery engineering
- AI production
- Serving and monitoring
Production stack
From product vision to resilient infrastructure.
We bridge product ambition to cloud reality with delivery, runtime, security, and AI.
Product and AI layer
Application services, LLM integrations, vector search, model endpoints, and data flows.
Delivery layer
Build pipelines, test gates, environment promotion, approvals, secrets, and rollback paths.
Runtime layer
Kubernetes, ingress, autoscaling, workload boundaries, and platform operations.
Cloud foundation
AWS or GCP accounts, networking, IAM, Terraform, data services, and cost visibility.
Reliability signals
Logs, metrics, traces, alerts, dashboards, and cost guardrails across the stack.
Approach
A practical path from assessment to production.
Discover & audit
Review architecture, cloud setup, workflows, and AI pipelines to find risk.
Design & blueprint
Engineer a practical infrastructure and AI deployment plan for your roadmap.
Build & integrate
Deploy cloud foundations, delivery systems, and AI layers alongside your team.
Harden & optimize
Lock down security, reduce cost, and verify reliability under pressure.
Transfer & upskill
Document the system so your team can operate it on its own.
Client fit
Built for teams at the point where growth becomes operationally serious.
Clean up cloud setups and automate delivery before infrastructure slows you down.
Prepare for smoother releases, better security, and clearer cost control.
Reduce risk when reliability becomes a business issue.
Harden clusters, pipelines, observability, and spend controls as usage grows.
Move prototypes into secure, scalable workflows.
Deploy model serving, vector search, latency controls, and cost monitoring.
Engagement examples
Infrastructure and AI systems built for production pressure.
Designed AWS/GCP infrastructure with Terraform, environments, networking, IAM, and deployment pipelines.
Improved cluster reliability, autoscaling, observability, security policies, and deployment workflows.
Built infrastructure for LLM-powered product features with secure APIs, monitoring, and scalable serving.
Production readiness
What gets hardened before systems meet real pressure.
Deployment safety
Repeatable releases, rollback paths, test gates, and clearer change ownership.
Cloud security
IAM boundaries, network posture, least-privilege access, and secure service exposure.
Operational visibility
Dashboards, alerts, logs, traces, and failure signals that keep engineering teams ahead of issues.
Cost and scaling control
Resource right-sizing, autoscaling, spend visibility, and AI usage monitoring.
Notes
Your systems should accelerate your growth, not hold it back.
Scaling should feel predictable. You shouldn’t fight infrastructure or worry that AI spikes costs.
Schedule a strategy callStart
Building something that needs to scale?
Talk to Xbase1 about cloud, AI, observability, and production readiness.
Book a strategy call