Web
- React
- Next.js
- TypeScript
- JavaScript
Technology stack
Technology chosen for the product, not the pitch.
We use proven tools to build simple websites, complex products, connected workflows, and dependable engineering foundations. The right stack follows the problem, team, risk, and operating reality.
The technology behind the work
A practical stack, explained clearly.
A non-technical buyer should be able to see the capability. A technical buyer should be able to see the depth.
Product interfaces
The experiences people see and use.
Mobile
- React Native
- Expo
- Kotlin
- Swift
Design systems
- Accessible UI
- Responsive design
- Component libraries
Application engineering
The software that powers products and workflows.
Languages and runtimes
- Node.js
- Python
- Go
- Java
Frameworks
- Fastify
- FastAPI
- Django
- Ruby on Rails
Service patterns
- REST APIs
- GraphQL
- tRPC
- OpenAPI
- gRPC
- Webhooks
- Event-driven systems
Cloud platforms
Hosting, compute, storage, networking, and secure operations.
AWS
- Lambda
- EC2
- ECS
- EKS
- Fargate
- RDS
- S3
- CloudFront
- API Gateway
- VPC
- IAM
Google Cloud
- Cloud Run
- GKE
- Compute Engine
- Cloud SQL
- BigQuery
- Pub/Sub
Microsoft Azure
- App Service
- Functions
- AKS
- Azure SQL
- Azure Storage
Data engineering and analytics
The data products, processing, and reporting that make operations measurable.
Databases
- PostgreSQL
- MongoDB
- DynamoDB
- Redis
Data pipelines
- ETL and ELT
- Apache Airflow
- dbt
- Dagster
- Dataflow
- Apache Spark
Analytics and processing
- BigQuery
- Redshift
- Snowflake
- Kafka
- Kinesis
- Reporting
- Product analytics
Search and graph
- Elasticsearch
- OpenSearch
- Neo4j
AI and automation
Practical intelligence with humans accountable for the result.
AI products
- OpenAI APIs
- Anthropic APIs
- RAG systems
- Evaluation workflows
Workflow automation
- Integrations
- Webhooks
- Queues
- Background jobs
Human controls
- Permissions
- Review steps
- Audit trails
Delivery and reliability
How software gets to production, stays observable, and recovers well.
Source control and CI/CD
- GitHub
- GitLab
- GitHub Actions
- GitLab CI/CD
- CI/CD pipelines
- Automated testing
Containers and infrastructure
- Docker
- Containers
- Kubernetes
- K8s
- Helm
- Terraform
Observability
- CloudWatch
- Prometheus
- Grafana
- OpenTelemetry
- Sentry
- Datadog
- Metrics, logs, and traces
- Alerts and incident response
Product operations
- Vercel
- Feature flags
- Monitoring
- Release management
Identity and security
- AWS Cognito
- Auth0
- Clerk
- Role-based access
- Secrets management
How we choose
The stack is a decision, not a shopping list.
We start with what the product must do and only add complexity where it earns its place.
Start with the operating need
Users, data, integrations, delivery speed, security, and the current team determine the useful foundation.
Use managed services where they help
A small team should not inherit infrastructure work that does not create product value.
Keep a path to scale
We make the important boundaries visible so the product can grow without a speculative enterprise rebuild.
Discuss the technical path
Bring the product question, not a fixed stack.
We can help turn a technical requirement into a practical delivery decision.
Frequently asked
Questions worth answering before the work begins.
Do we need to choose a technology stack before we talk?
No. Bring the product, workflow, current systems, constraints, and the outcome you need. We will make the technical choices visible and explain the trade-offs.