AWS & Azure Architecture
Cloud-native infrastructure design on AWS and Azure — from VPC, networking, and identity to multi-region deployment.
We design AI assistants, chatbots, and automation connected to real data and workflows — with guardrails, audit logs, and stable operations foundations from day one.
AI delivers value on a stable, secure, monitored foundation.
Cloud-native infrastructure design on AWS and Azure — from VPC, networking, and identity to multi-region deployment.
EKS, AKS, GKE — design, deploy, and operate Kubernetes clusters for real production workloads.
We design AI assistants, chatbots, and automation connected to real data and workflows — with guardrails, audit logs, and stable operations foundations from day one.
Behind FlowNexa
Lead Engineer / Founder
FlowNexa is led by an engineer with 17+ years delivering AI assistants, chatbots, automation, and system integration for SMBs — on production-ready cloud, Kubernetes, and DevSecOps foundations.
Designed for reliability, monitoring, maintainability, and real operations — not only demos.
Guardrails, access control, audit trail, and safe workflow boundaries are considered from the beginning.
Jenkins, ArgoCD, GitHub Actions, GitLab CI — automated pipelines from commit to production with clear rollback.
Security from code to cluster: secret management, vulnerability scanning, access control, and audit trails.
Prometheus, Grafana, Loki, OpenTelemetry — full-stack visibility from infrastructure and applications to AI workflows.
Tagging, rightsizing, and workload-aware cost governance — transparent and optimised over time.
Assistants, RAG, knowledge bases, and chatbots connected to CRM, PMS, and Zalo/Facebook channels.
n8n, API, and webhook automation for repetitive tasks with human approval when needed.
Access control, audit trails, and safe deployment boundaries for AI in production.
CI/CD, Kubernetes, monitoring, and rollback — infrastructure that scales with your AI workloads.
Start small with high-impact use cases, then expand based on measurable business value.
A clear assessment to identify use cases, data readiness, risk, cost, and MVP roadmap.
Start with a practical consultation to identify the right AI use case, required data, integration approach, risk boundaries, and MVP roadmap.
We onboard at most three new customers per month to protect delivery quality.