Proven tools, chosen for the problem
We pick technology your own team can hire for and maintain long after we hand over.
Technologies we use
Java & Spring
High-throughput services and event-driven systems.
Microsoft .NET
Enterprise APIs and .NET Framework upgrades.
Node.js
Lightweight APIs and real-time services.
React
Fast, accessible interfaces and shared design systems.
TypeScript
Typed front ends from Angular rewrites to new builds.
Kubernetes
Container platforms on EKS and AKS.
Terraform
Every environment defined in code and rebuildable from Git.
CI/CD
Pipelines that test, scan and deploy every merge.
Containers
Reproducible builds from laptop to production.
Snowflake
Cloud warehouses, modeled and tested with dbt.
Databricks
Lakehouse storage, Spark jobs and ML pipelines.
Kafka
Event streaming between services and into analytics.
Python & AI
Model serving, document AI and forecasting.
PostgreSQL
Our default database, until a workload proves it needs another.
How we choose a stack
Three questions decide it. The answers go into an architecture decision record you keep.
Can your team hire for it?
We favor widely used languages and frameworks over niche ones, even when the niche option is slightly faster.
Does it fit what you already run?
A Microsoft shop gets .NET and Azure unless there is a measured reason to change.
Will it be boring in five years?
We avoid tools that are new this year for anything on the critical path.