Data Engineering and Integration
Break down data silos and unlock the full potential of your operational information. Stop starting every new initiative with painful data extraction.
When data is locked inside incompatible legacy systems, every digital project becomes a migration effort before real work can begin.
Select the challenge that best reflects your situation to see how we address it.
Analytics, automation, and AI projects fail to launch because data is inaccessible or unreliable.
Every new project begins with months of extraction, cleaning, and reconciliation.
Different systems report different numbers, eroding trust in the data.
Business impact
Real cost
€200K+ in failed project investments, 6-12 month delays on critical initiatives
Business impact
Real cost
40-60% of project budgets spent on data preparation instead of value creation
Business impact
Real cost
Missed optimization opportunities worth €100K+ annually per asset
Mateusz Wilczyński
CTO at Exlabs

To unlock the value of your data, we design and build modern data platforms that connect legacy systems with cloud-native analytics capabilities.
We integrate existing systems without disrupting day-to-day operations.
Secure API connections to operational systems
Real-time and batch data synchronization
Data validation and quality checks at the source
A cloud-native data foundation designed for scale, performance, and reliability.
Scalable storage without impacting operational systems
Automated ETL / ELT pipelines
Built-in governance, security, and audit trails
A clean, consistent data foundation that supports everything you build next.
Standardized data models across domains
Real-time availability for dashboards and advanced analytics
Self-service access for business users
Technology choices are guided by pragmatism and experience. The stack is selected to ensure reliability, performance, and long-term maintainability for critical systems.
Robust tools like Apache Kafka and Spark are utilized to handle complex streams and enable real-time analysis.

D3.js

Plotly

Charts.js

Power BI

Grafana

Metabase

Airbyte

dbt

Airflow

Snowflake

Databricks
Architecting on AWS and Azure with Infrastructure as Code (Terraform) for secure, automated, and repeatable environments.

Apache Kafka

Airbyte

dbt

Airflow

Snowflake

Databricks

PostGis
Building on modern, scalable frameworks (Go, Python, TypeScript) and best practices like containerization with Docker.

React.JS

Next.js

Nest.js

Typescript
Node.JS

JavaScript

GraphQL

PostgreSQL

Redis

Python

Docker
Terraform
Kubernetes

Github Actions

Playwright

AWS

Azure

Our process is designed for transparency and results. We turn fragmented data landscapes into production-ready platforms through a structured, four-step approach.
Real outcomes from production systems solving high-stakes operational challenges.
Explore how custom software and data platforms are built to solve complex challenges for organizations operating at scale.
Everything you need to know before you decide to work with us.
We typically start within 2–3 weeks from the first conversation. The timeline depends on how quickly we can run the technical assessment workshop (usually within a few days) and finalize the commercial agreement.
For urgent situations, we’ve started projects in as little as one week. We never skip discovery — rushing into development without proper scoping leads to costly delays later.
Your project team usually consists of 2–4 people depending on scope: a Technical Lead, a Frontend or Data Engineer, and a Project Manager. For complex initiatives, we add specialists as needed.
You’ll meet your dedicated team during kickoff, and they remain your consistent points of contact throughout the project.
We work in two-week sprints with clear milestones. You’ll have a weekly check-in call to review progress and priorities. Between calls, communication happens via Slack or email.
At the end of each sprint, you see working software — not just status updates.
For well-defined projects, we offer fixed-price delivery with milestone-based payments.For exploratory work, we use time-and-materials with a clear monthly budget cap.
We’re transparent about costs from day one and flag any scope changes early.