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Services · Cloud, infrastructure & data

Cloud, infrastructure and data platforms that hold up under load.

Architecture, DevOps and data engineering for products that handle real traffic — from a first production environment to a platform processing terabytes a day.

Discuss your projectSee related cases
Proof from our cases
1+ TBprocessed every day on a platform we deployed
4×lower cloud cost on a telecom telemetry system
5,000+devices connected through one pool
How it fits together

From raw events to decisions, on a platform that stays up.

A typical data platform has five stages from source to decision, with the engineering that keeps it running underneath.

1 · COLLECTSourcesApps, events, devicesDatabases, partner APIs2 · MOVEStreamKafkaBuffers, routes events3 · PROCESSOrchestrateAirflowSchedules, transforms4 · KEEPStoreClickHouse · IcebergLakehouse, fast queries5 · DELIVERServeBI, APIs, MLDashboards, ML featuresQuality checks, lineage and alerts feed back into the pipelineTHE PLATFORM UNDERNEATHInfrastructure as codeTerraformCI/CD pipelinesGitHub ActionsObservabilityGrafanaContainersDocker · KubernetesCost controlCloud cost reviewsSecurity and accessLeast privilege, audit trail
  1. SourcesApps, events, devices
  2. StreamKafka: buffers and routes events
  3. OrchestrateAirflow: schedules and transforms
  4. StoreClickHouse and Iceberg: lakehouse and fast queries
  5. ServeBI, APIs and ML features
The platform underneath
Infrastructure as codeCI/CD pipelinesObservabilityContainers and KubernetesCost controlSecurity and access

This is the typical shape, not a template. We change the parts to fit your load, your team and your budget.

Technologies behind this work
Apache Kafka
ClickHouse
Apache Iceberg
Apache Airflow
PostgreSQL
Python
Docker
Kubernetes
Terraform
GitHub Actions
Grafana
Google Cloud
What is included

Four areas, one engineering team.

Pick one or combine them. Each item is scoped to your system.

Cloud & infrastructure

The foundation your product runs on.
  • Cloud infrastructure engineering
  • Cloud architecture & cloud-native engineering
  • Infrastructure as code
  • Containers & Kubernetes
  • Cloud orchestration
  • Platform engineering

Delivery & reliability

Ship often, and keep it up.
  • DevOps engineering & consulting
  • CI/CD pipelines
  • Monitoring & observability
  • Site reliability engineering
  • Disaster recovery & resilience

Data platforms

From raw events to decisions.
  • Data strategy & architecture
  • Data engineering & pipelines
  • Warehouses & data lakes
  • Data governance, quality & observability
  • BI & reporting

Performance & cost

Faster, steadier, cheaper to run.
  • Performance & scalability optimization
  • Database engineering
  • FinOps & cloud cost optimization
Typical situations

When teams come to us.

Cost

Your cloud bill keeps growing

We trace where the money goes, then redesign what is wasteful, without touching the data flows the business relies on.

Throughput

Data arrives faster than the system can process

We design the pipelines, storage and processing for the volume you have now and the volume you expect.

Delivery

Releases are manual and risky

We automate build, test and deploy, and add the monitoring that tells you something broke before your users do.

What you get

Deliverables you will keep.

Concrete artifacts, documented and handed over.

A reproducible infrastructure setup
A CI/CD pipeline
A monitoring and alerting stack
A documented production environment
Data pipelines and a warehouse or lake
An optimized database
A cost dashboard and a savings plan
A disaster-recovery plan
A handover your own team can run
How to start

Three ways to begin.

Larger work starts with a short paid discovery.

All offers
Engagement

AI / Data / Cloud Modernization Engagement

Modernize workflows, data, AI systems and cloud architecture.

Custom scope
Engagement

Product Engineering Support

Senior engineers across frontend, backend, cloud, QA and AI/data, month by month.

Monthly
Engagement

Dedicated Product Squad

A multi-role team on a clear mission, with its own delivery cadence.

3-month minimum, then monthly
Proof

Work you can open and check.

See all 7 case studies
1+ TB/day
processed in real time
Urban-Intel data platform
A real-time platform turning a terabyte of daily data into operational decisions.
4×
lower cloud cost
Telecom telemetry & accounting
A mission-critical real-time system for a top-three telecom provider.
15
architecture decisions
iGaming enterprise data platform
Kafka, ClickHouse, Iceberg and Airflow, with data contracts and governance.
Where this ends

Not quite what you need?

Moving a running system to another platform?Architecture & modernizationNeed someone to run it day to day?Managed services & supportWant AI or machine learning on top of the data?AI, automation & agents
FAQ

Questions about cloud and data work.

Do you run the infrastructure after launch?
We can hand it to your team with documentation and runbooks, or continue with ongoing support as a separate monthly engagement.
Which cloud providers and tools do you work with?
Our published data work uses Kafka, ClickHouse, Apache Iceberg and Airflow, with PostgreSQL, Python and Node.js services around them. Provider and orchestration specifics depend on the system, so tell us yours and we will say plainly whether it is a fit.
Can you start with an audit of what we have?
Yes. A short paid discovery maps the system, the load and the bill, and ends with a prioritized plan. Larger work starts there.
How do you protect production while changing it?
In small steps. The data flows the business relies on keep running, every step has a way back, and monitoring is in place before the change, not after it.

Tell us about your system.

Describe the platform, the load or the bill. We reply with a clear next step — usually within 24 hours.

Discuss your projectBook a routing call