Technology We Use
The platforms, languages and tools our products and client engagements are built on.
- 3
- Major Clouds
- 18
- Products Built
- Cloud + on-prem
- Deployment
- Post-launch
- Support Model
Amazon Web Services
The most common deployment target for our products and client platforms. We design for managed services where they reduce operational load, and for portability where a client needs it.
- EC2 / Lambda
- RDS / DynamoDB
- S3 / CloudFront
- EKS / Fargate
Microsoft Azure
Used where a client's estate is already Microsoft-centric, or where the work involves Active Directory, .NET or Microsoft data tooling.
- Azure DevOps
- Cosmos DB
- Azure AI
- Active Directory
Google Cloud Platform
Our preferred home for data-heavy work: warehousing, analytics pipelines and ML training on managed infrastructure.
- BigQuery
- GKE
- Vertex AI
- Firebase
Application Stack
The languages and frameworks we build products and client systems in, chosen per project rather than by habit.
- React / TypeScript
- Node.js
- .NET
- Java / Spring
- Python
Data and Storage
Relational where integrity matters, document and time-series stores where the data shape calls for them, and a warehouse layer for reporting.
- PostgreSQL
- SQL Server
- MongoDB
- Redis / TimescaleDB
Observability and Delivery
Pipelines, containers and monitoring assembled into a delivery setup the client's own team can operate after handover.
- GitHub Actions / GitLab CI
- Docker / Kubernetes
- Terraform
- Grafana / Datadog
Have a Stack Constraint?
If you must build on a specific platform or language for policy reasons, tell us — we will be straight about whether we are the right fit.