Data platforms that stay reliable at billions of events a day.
We design and build data platforms that handle real-world scale — from raw ingestion to live dashboards — so your teams always have the data they need to decide.
What we build
Three practice areas
From sensors and event streams to the time-series stores and live dashboards your operations run on.
Data engineering
We build the pipelines that move, transform, and deliver your data — batch at scale and in real time. ETL/ELT from any source, streaming with Kafka and Spark, and lakehouses on Databricks and Amazon S3. Data quality and lineage included.
Data warehouse & modeling
We design dimensional models on Snowflake, BigQuery, and Redshift, bring in data from operational systems and third-party APIs, tune query performance, and set governance rules that hold as the data grows.
BI & analytics
We turn raw data into dashboards and reports that decision-makers actually use. Interactive, always connected to live data, and designed for self-service — so teams stop waiting on data requests.
How it fits together
From where most teams start to what we build
Typical starting point
Sources
Nightly batch exports
Storage
One overloaded database
Insight
Dashboards a day late
What we build
Sources
Sensors · APIs · CRM
Streaming
Apache Kafka
Apache Spark
Storage
Time-series store
InfluxDB
Lakehouse
Databricks · Amazon S3
Insight
Grafana
live dashboards
BI
Amazon QuickSight
From nightly exports to data that arrives as it happens: streamed through Kafka and Spark into stores built for the question, and in front of people in near real time. The Iseatec and Atigeo cases show it in practice.
Case studies
Work that shipped
Selected data platform projects from our case studies.
Client
Iseatec
Scope
Real-time IoT sensor data platform on AWS
Built an end-to-end platform ingesting billions of sensor events per day using Apache Spark and InfluxDB. Query time reduced by over 40% through time-series optimization. 99.9% uptime with Terraform-automated infrastructure and Grafana dashboards providing real-time operational visibility.
Client
Oves Enterprise
Scope
Petabyte-scale Cloudera/Spark stabilization
Identified and fixed root causes of corruption in a petabyte-scale Cloudera distribution. Optimized Spark job algorithms, enabling daily job runs that were previously too slow. Migrated from Cloudera to vanilla Hadoop with an HA master, eliminating vendor lock-in entirely.
Client
Professional Support Technologies
Scope
End-to-end AWS data platform: ETL, ML, and BI
Delivered a unified data platform covering the full lifecycle — raw ingestion through ETL to ML models and executive BI dashboards. Built on AWS with SageMaker for real-time predictions and QuickSight for cross-departmental reporting.
Two minutes, no email required
How reliable is your data platform?
Six questions; “Not sure” is a fine answer. You get the score and the fixes straight away. We keep your answers without your name or email, to improve the check, and if you then contact us from this tab, we attach them so the engineer can prepare.
Freshness
Question 1 of 6
How fresh is the data your teams look at?
Filling in as you answer
Freshness
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Failures
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Schema changes
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Reprocessing
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Scale
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Ownership
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How we engage
Four ways to work with us
Start with a fixed-scope audit, scale into a project, keep us on to run it. Engineers on every call — there is no sales team.
2 weeks · fixed scope
Data Platform Audit
A structured review of your current data architecture: pipeline reliability, warehouse design, cost efficiency, and analytics gaps. Delivered as a prioritized roadmap with effort estimates.
6–16 weeks
Pipeline & Warehouse Build
Fixed-scope delivery of a data pipeline, warehouse layer, or BI system. Clear milestones, weekly check-ins, handover with full documentation and runbooks.
Monthly · inside your team
Embedded Platform Engineers
One engineer or a full squad — sized to the roadmap, month by month. Senior engineers join your team, your tools, and your rituals, led by the same architect from day one.
Monthly · we run it
Managed Platform Operations
Senior engineers own your platform in production: on-call for incidents, with response times written into the contract (24/7 if you need it), upgrades, security patching, capacity and cost reviews, and a monthly written report. Your team keeps shipping features.
Our standards
What we don't do
We work with companies that are serious about their data. That means being direct about the shortcuts we won't take.
Warehouses without data-quality checks — garbage in, garbage out
Dashboard sprawl disconnected from a reliable source of truth
Pipelines that work in dev but fail silently in production
Proprietary lock-in where an open standard would serve you better
Ready to talk about your data platform?
A direct conversation about where your data is today and where it needs to be.
Book a free 45-min architecture review45 minutes with a senior engineer: your setup, the risks, what to fix first. No sales team.