Data Engineering and Integration

Trapped Data Killing 
Your Digital Initiatives?

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.

Show Me How

The Hidden Cost of Data Silos

Select the challenge that best reflects your situation to see how we address it.

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Stalled Digital Initiatives

Analytics, automation, and AI projects fail to launch because data is inaccessible or unreliable.

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Manual Data Wrestling

Every new project begins with months of extraction, cleaning, and reconciliation.

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Inconsistent Decision Making

Different systems report different numbers, eroding trust in the data.

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Business impact

Missed competitive advantages.

Real cost

€200K+ in failed project investments, 
6-12 month delays on critical initiatives

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Business impact

Project delays, resource drain, technical debt accumulation

Real cost

40-60% of project budgets spent on data preparation instead of value creation

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Business impact

Poor strategic decisions, operational inefficiencies, stakeholder confusion

Real cost

Missed optimization opportunities worth €100K+ annually per asset

Let's discuss your specific challenge and outline 
a clear path forward.

Mateusz Wilczyński

CTO at Exlabs

Schedule a Technical Call
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Unified Data Architecture That Actually Works

To unlock the value of your data, we design and build modern data platforms that connect legacy systems with cloud-native analytics capabilities.

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Legacy System Integration

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

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Modern Data Platform

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

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Analytics-Ready Data Layer

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

Pragmatic and Proven Technology

Technology choices are guided by pragmatism and experience. The stack is selected to ensure reliability, performance, and long-term maintainability for critical systems.

Data & Analytics Engineering

Robust tools like Apache Kafka and Spark are utilized to handle complex streams and enable real-time analysis.

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D3.js

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Plotly

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Charts.js

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Power BI

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Grafana

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Metabase

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Airbyte

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Airflow

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Snowflake

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Databricks

Cloud & Infrastructure

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

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Apache Kafka

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Airbyte

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dbt

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Airflow

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Snowflake

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Databricks

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PostGis

Custom Software Development

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

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React.JS

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Next.js

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Nest.js

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Typescript

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Node.JS

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JavaScript

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GraphQL

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PostgreSQL

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Redis

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Python

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Docker

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Terraform

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Kubernetes

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Github Actions

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Playwright

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AWS

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Azure

Partnering with the Leading Cloud Platforms
Turning Technical Blueprints into Production Reality
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From Data Chaos to Unified Platform

Our process is designed for transparency and results. We turn fragmented data landscapes into production-ready platforms through a structured, four-step approach.

1

Architecture Audit & Data Mapping

  • Analyze existing systems and data flows

  • Document data sources, formats, and integration points

  • Identify data quality issues and bottlenecks

  • Map governance and compliance requirements

Outcome

Complete current-state architecture documentation

Identified integration opportunities

Clear technical requirements for a unified data platform

2

Target Architecture Design

  • Design a scalable, cloud-based data architecture

  • Define ETL / ELT processes and transformation logic

  • Establish data governance and security frameworks

  • Plan migration with minimal operational disruption

Outcome

Detailed technical blueprint for new data platform

Migration plan with risk mitigation strategies

Approved architecture ready for implementation

3

Implementation 
& Data Migration

  • Build new data pipelines and processing infrastructure

  • Implement data cleansing and validation processes

  • Conduct controlled migration of historical data

  • Establish real-time data synchronization from 
operational systems

Outcome

Functioning unified data platform with live operational data

Validated data integrity and quality assurance

Automated data processing workflows

4

Monitoring & Quality Assurance

  • Deploy data quality monitoring and alerting systems

  • Establish maintenance procedures and documentation

  • Train internal teams on platform operation

  • Set up ongoing support and optimization processes

Outcome

Stable, monitored data platform serving as "single source of truth"

Internal team capable of platform maintenanceTeams confident using new reporting capabilities

Foundation ready for analytics and AI initiativ

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From Technical Blueprints to Production Reality

Real outcomes from production systems solving high-stakes operational challenges.

< 3 months

Decision cycles reduced

Accelerated strategic decisions by transforming months of analysis into real-time insights.

Learn how we accelerated decisions

3,000+

UK air quality zones automated

Eliminated manual workflows, enabling scalable, 
real-time operational oversight.

Learn how we built for scale

26+ GWhs

Battery storage operations optimized

Production-ready architectures enabling reliable, compliant, and efficient operations.

Learn how we handled complexity

Our Work in Production

Explore how custom software and data platforms are built to solve complex challenges for organizations operating at scale.

From Complex Data to Competitive Dominance

How CRU Group partnered with Exlabs to de-risk large-scale investment decisions through production-ready data platforms.

90% Reduction in Analysis Time
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Emobility infrastructurefor CleanAirZones around 
UK Local Authorities

We built a scalable, serverless infrastructure enabling the UK Government to control vehicle access to Clean Air Zones nationwide.

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The Asset Platform 
GIS & UX Upgrade Story

Major GIS and UI upgrade with globe view, optimised performance, and enhanced UX—resulting in smoother navigation and better asset insights.

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Scaling Open-Source Grid Insights Across Europe

Turning raw grid data into actionable, open-source intelligence

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Explore more of our projects
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Frequently Asked Questions

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.