From data pipeline to user interface
We build the full stack: cloud infrastructure, data engineering, backend services, APIs, and custom interfaces. Every project is scoped, architected, and delivered by senior engineers — not templated and handed to juniors.
Cloud Development
We design and build cloud-native applications on AWS, Azure, and Google Cloud Platform. Our cloud work includes:
- Containerized applications — Docker, Kubernetes, and managed container services (ECS, GKE, AKS)
- Serverless architectures — Lambda, Cloud Functions, Cloud Run — for event-driven systems with minimal operational overhead
- Infrastructure as code — Terraform and cloud-native IaC tools, so your infrastructure is reproducible, reviewable, and version-controlled
- Cloud-native APIs — REST and event-driven backends designed to scale without vertical limit
We design for scale from day one, without over-engineering for scale you do not yet need.
Big Data & Analytics Engineering
When data volumes exceed what a standard database can handle efficiently, or when the value is in the patterns rather than the records, you need a purpose-built data stack.
We build:
- Batch and streaming pipelines — ingesting data from operational systems, external APIs, event streams, and files into a reliable, queryable store
- ETL/ELT architectures — using dbt, Apache Spark, Airflow, and cloud-native equivalents to transform raw data into clean analytical models
- Data warehouses and lakehouses — BigQuery, Redshift, Snowflake, Delta Lake — designed for query performance and cost efficiency
- Analytics-ready data models — dimensional models, slowly changing dimensions, and aggregation layers that your BI tools can query without custom SQL every time
The result is a data stack your team can own: documented, testable, and designed to grow with your organization.
Custom Software
When generic tools do not fit your process, we build tools that do:
- Workflow automation applications — guides users through defined steps, captures structured data, triggers downstream actions
- Internal dashboards and operational portals — purpose-built interfaces that surface exactly what your teams need, nothing they don’t
- Process portals — user-facing applications that make complex backend operations accessible to non-technical staff
- Custom interfaces for Véloce Workflow — purpose-built frontends for specific teams or processes, powered by the Véloce API
APIs & Microservices
- RESTful APIs — well-documented, versioned, and designed for integration from day one
- GraphQL — for frontends that need flexible data fetching without multiple round trips
- Event-driven services — Kafka, AMQP, or cloud-native message queues for systems that communicate asynchronously
- Internal SDKs and client libraries — when your internal teams need to integrate with a service you own
Technologies
| Layer | Stack |
|---|---|
| Languages | Python, Go, Node.js, Java |
| Frontend | React, Vue |
| Cloud | AWS, Azure, GCP |
| Containers | Docker, Kubernetes |
| IaC | Terraform |
| Data processing | Apache Spark, dbt, Airflow |
| Data warehouses | BigQuery, Redshift, Snowflake |
| Databases | PostgreSQL, MySQL, MongoDB, Redis |
| Messaging | Kafka, RabbitMQ, SQS, Pub/Sub |
How We Work
Iterative delivery: working software early, feedback incorporated, no six-month waterfall. Every project includes requirements analysis, architecture review, implementation, deployment support, and knowledge transfer.
We write clean, maintainable code. Documentation is part of the deliverable, not an afterthought.