Machine learning isn’t just a trend – it’s become the backbone of smarter decision-making. Across Europe, a growing pool of engineering-focused teams is quietly reshaping how industries approach automation, forecasting, and operational clarity. It’s no longer about experimenting with models in isolation. What matters is integration – systems that actually run in production and adapt to messy, real-world inputs.
This list highlights firms that go beyond surface-level AI. These are teams that focus on getting ML into pipelines, dashboards, and tools people actually use. No fluff. Just well-built systems designed to work.
1. A-listware
A-listware works with companies across Europe to deliver data-driven systems built on machine learning and applied analytics. Our focus is on operational clarity – not just building models, but making sure they integrate well with your internal tools and workflows. Whether it’s part of a product build, a research tool, or a data pipeline, we stay close to the engineering side of the process to avoid unnecessary complexity and keep the deliverables usable.
Machine learning and analytics are not standalone services for us – they’re part of a broader software development offering. That’s why the work often sits inside long-term projects, embedded into infrastructure or paired with custom applications. We also help with team augmentation when clients need specific ML/AI specialists but want to keep delivery under one roof. This flexibility allows us to contribute to both large transformation efforts and focused pilots.
Key Highlights:
- Local coordination across multiple European markets
- Embedded analytics inside full product builds
- Hands-on model integration, not just model design
- Experience with hybrid and cloud-native systems
Services:
- Machine learning model implementation
- Data pipeline setup and transformation workflows
- Predictive analytics tooling and dashboards
- Team augmentation for ML/AI roles
- Model testing, deployment, and integration
- Root cause analysis and documentation
Contact Information:
- Website: a-listware.com
- E-mail: info@a-listware.com
- Facebook: www.facebook.com/alistware
- LinkedIn: www.linkedin.com/company/a-listware
- Address: St. Leonards-On-Sea, TN37 7TA, UK
- Phone: +44 (0)142 439 01 40
2. ML Analytics
Based in Portugal, ML Analytics builds custom ML systems with a strong focus on decision modeling and real-world outcomes. Projects typically bring together data scientists and business analysts to co-develop models grounded in actual use cases – not just theoretical predictions.
Rather than offering plug-and-play tools, the team takes on more of an embedded R&D role. That includes building explainable models for aerospace, telecom, and retail sectors – with particular attention paid to validation and fine-tuning. Most collaborations feel less like outsourcing and more like adding a hands-on research partner to the team.
Key Highlights:
- Portuguese HQ, but work spans multiple EU verticals
- Emphasis on prescriptive analytics and real-time decisions
- Recognized for innovation and research depth
- Strong stance on explainable AI and validation standards
Services:
- Custom machine learning model development
- Predictive and prescriptive analytics
- Model verification and failure mode diagnosis
- Optimization scenario modeling
Contact Information:
- Website: mlanalytics.pt
- E-mail: geral@mlanalytics.pt
- Twitter: x.com/ml_analytics
- LinkedIn: www.linkedin.com/company/ml-analytics
3. Dev Centre House
Dev Centre House, operating out of Ireland, builds end-to-end machine learning systems for businesses that need smarter automation, cleaner insights, or more efficient processes. Projects range from deep learning and predictive modeling to computer vision and NLP – all the way through to final deployment.
Cloud-native delivery is a strong suit. Platforms like AWS, Azure, and Google Cloud are baked into the workflows from day one. A typical engagement starts structured but leaves space to flex – whether that’s spinning up a short-term proof of concept or launching a larger initiative. Post-launch, the focus shifts to iteration: tuning, monitoring, retraining, and performance feedback.
Key Highlights:
- Operates in Ireland with outreach across EU and US markets
- Certified experience with AWS, Azure, and GCP ML services
- Combines R&D exploration with production-grade delivery
- Covers full ML lifecycle: data to deployment
Services:
- Machine learning model training and deployment
- Deep learning for image, speech, and NLP tasks
- Predictive analytics and business insight modeling
- Computer vision and OCR development
Contact Information:
- Website: www.devcentrehouse.eu
- E-mail: hello@devcentrehouse.eu
- Facebook: www.facebook.com/devcentrehouse
- Twitter: x.com/DevCentreHouse
- LinkedIn: www.linkedin.com/company/devcentrehouse
- Address: Suite 5, Plaza 256, Blanchardstown Corporate Park 2, Dublin 15, D15 VE24, Ireland
- Phone: +353 1 531 4791
4. Trustsoft
Trustsoft, based in the Czech Republic and Switzerland, builds machine learning pipelines and analytics platforms as part of its cloud-native service portfolio. Their ML work is often tied into broader infrastructure efforts, with solutions running on AWS-native tools and built to scale. Projects are aimed at helping clients automate internal decisions, enable real-time dashboards, or support product personalization.
What stands out is the full-stack approach. Instead of stopping at model development, the team connects ML with the full data lifecycle – ingestion, transformation, governance, cataloging. This makes the output usable across departments, not just technical teams. Many projects continue over time, evolving as the data platform matures.
Key Highlights:
- Teams work out of Czechia and Switzerland
- Specializes in AWS-native analytics and automation
- End-to-end ML pipelines, from ingestion to dashboards
- Helps shape full data ecosystems, not just isolated models
Services:
- Machine learning pipeline development
- Business intelligence dashboard integration
- Real-time analytics and automation
- ML model training with Amazon SageMaker
Contact Information:
- Website: www.trustsoft.eu
- E-mail: info@trustsoft.eu
- LinkedIn: www.linkedin.com/company/trustsoft
- Address: Karolinská 661/4, 186 00 Praha 8, Czech Republic
5. IntelliSoft
IntelliSoft builds tailored machine learning solutions aimed at making operations smarter, faster, and more data-informed. There’s a strong engineering mindset behind it – each project blends model design with preprocessing and scalable infrastructure, rolled out as part of a continuous delivery setup. Some builds are standalone models, others are full-cycle AI systems folded into the core product.
The team covers a wide spectrum – predictive models, deep learning, reinforcement learning, image and video recognition. Projects often require input from both technical and business teams, so structured collaboration is baked into the workflow. PMs help keep alignment between data scientists and industry stakeholders as things move from idea to deployment.
Key Highlights:
- Proven track record with complex ML projects
- Flexible formats: standalone models or full system integration
- Post-launch support and model health monitoring
- Works with TensorFlow, PyTorch, Azure ML, SageMaker, and more
Services:
- Predictive analytics and forecasting
- Deep learning and reinforcement learning solutions
- Image and video recognition
- Data preparation and preprocessing
Contact Information:
- Website: intellisoft.io
- E-mail: swiss@intellisoftware.net
- Address: Bernstrasse 15, 8952 Schlieren, Switzerland
6. N-iX
N‑iX delivers machine learning and analytics services through its network of engineering centers in Eastern Europe. Much of the work focuses on making data pipelines usable and productive – helping companies move from scattered datasets to insights that actually inform decisions. ML is usually part of a bigger ecosystem, including ingestion layers, storage, visualization, and governance.
Projects cover a wide range – NLP, anomaly detection, recommendation engines, and generic models – all built to run in cloud-native or hybrid setups. Teams also take on legacy platform migrations, helping shift outdated analytics stacks to scalable architectures. For orgs without in-house data teams, N‑iX supports roadmap planning and stack selection too.
Key Highlights:
- Strong delivery base across Eastern Europe
- Experience across AWS, Azure, and Google Cloud
- Connects ML with warehousing, governance, and reporting layers
- Full-cycle delivery: from design to tuning
Services:
- ML model development and integration
- Data warehouse and lakehouse setup
- NLP, chatbots, and recommender systems
- Predictive maintenance and anomaly detection
Contact Information:
- Website: www.n-ix.com
- E-mail: contact@n-ix.com
- Facebook: www.facebook.com/N.iXUKR
- Twitter: x.com/N_iX_Global
- LinkedIn: www.linkedin.com/company/n-ix
- Address: 43A Ul. Zabłocie, Krakow, Poland
- Phone: +442037407669
7. Lemberg Solutions
Lemberg Solutions works at the intersection of machine learning and applied problem-solving. The projects here usually lean practical – computer vision for smarter image processing, predictive maintenance to reduce downtime, and ML-driven recommendation engines that feel more relevant. Most builds start small with a proof of concept, then scale once the approach has been validated in real-world conditions.
Engineering work goes hand in hand with business context. Early on, the team helps shape the ML strategy before diving into technical buildout. The company’s footprint spans industries like healthcare, logistics, industrial IoT, and energy. Alongside model development, infrastructure setup and backend integration are part of the package.
Key Highlights:
- Hands-on experience across healthcare, logistics, and industrial ML
- Supports full cycle: PoC, data engineering, deployment
- ISO 27001 and 9001 certified for security and quality
- Delivers CV, automation, and predictive tools
Services:
- Custom ML model design and training
- Smart automation and process optimization
- Computer vision and image classification
- Predictive maintenance tools
Contact Information:
- Website: lembergsolutions.com
- E-mail: info@lembergsolutions.com
- Facebook: www.facebook.com/LembergSolutions
- Twitter: x.com/WeAreLemberg
- LinkedIn: www.linkedin.com/company/lembergsolutions
- Instagram: www.instagram.com/lembergsolutions
- Address: Am Sandtorkai 32, Hamburg, Germany
- Phone: +49 403 346 62 17
8. InData Labs
InData Labs gets involved early – often before a single line of code has been written. Most projects kick off with discovery work: figuring out feasibility, estimating impact, and aligning goals. From there, the focus shifts to model development, backend integration, and rolling everything out in the cloud. A lot of what’s built ends up inside mobile or web apps, with AI embedded in the flow.
Work here combines data science, DevOps, and full-stack software skills. Some projects are full product builds; others focus on one piece – like scaling an existing model or rearchitecting for better performance. Industry-wise, the team covers a lot: logistics, fintech, e-commerce, media, and more.
Key Highlights:
- Strong focus on early-stage AI design and architecture
- Builds both standalone models and app-integrated solutions
- AWS-certified cloud deployment partner
- Covers full AI lifecycle: from training to post-launch support
Services:
- Custom machine learning model development
- Predictive analytics and optimization
- AI system architecture and integration
- AI-driven mobile and web application development
- Cloud deployment and scaling
Contact Information:
- Website: indatalabs.com
- E-mail: info@indatalabs.com
- Facebook: www.facebook.com/indatalabs
- Twitter: x.com/InDataLabs
- LinkedIn: www.linkedin.com/company/indata-labs
- Address: Ukmergės g. 126, 08100, Vilnius
- Phone: +370 520 80 9 80
9. Protiviti
Protiviti brings machine learning into highly structured environments – finance, healthcare, government – where risk, compliance, and governance matter as much as the algorithms themselves. Projects usually start with architecture planning and privacy frameworks, then expand into forecasting models, automation flows, and reporting systems.
This isn’t just about writing code – there’s usually a broader transformation effort happening. AI gets tied into regulatory readiness, cloud modernization, or operational controls. Advisory support is part of the deal, too. In many cases, teams rely on Protiviti to guide both the tech and the strategy behind it.
Key Highlights:
- Focus on compliance, governance, and enterprise-grade AI
- Mixes consulting and delivery in regulated sectors
- Handles both technical rollout and strategic planning
- Works closely with AWS, Microsoft, and Oracle
Services:
- Advanced analytics and AI consulting
- Enterprise data governance and architecture
- Predictive modeling and scenario analysis
- Data visualization and decision support
Contact Information:
- Website: www.protiviti.com
- E-mail: contact@protiviti.ch
- Facebook: www.facebook.com/Protiviti
- Twitter: x.com/protiviti
- LinkedIn: www.linkedin.com/company/protiviti-switzerland
- Address: Bahnhofpl. 9, 8001 Zürich, Switzerland
- Phone: +41 43 344 76 41
10. Harnham
Harnham isn’t building ML models – it’s building the teams behind them. This is a recruitment firm with a tight focus on data and analytics talent, especially in machine learning, data science, and AI roles. Instead of delivering solutions, the work here is about matching skilled specialists with the right environments – whether that’s a startup scaling fast or an enterprise growing its internal analytics capabilities.
Recruitment covers both permanent hires and contract placements, and it’s not limited to one sector. Finance, gaming, healthtech, retail – the demand’s there across the board. What makes this group stand out is the mix of market intel and hands-on hiring – companies often lean on them to tweak internal talent strategies, not just fill roles.
Key Highlights:
- Focused on recruitment for ML, data science, and AI roles
- Active in the UK, Europe, and US markets
- Covers everything from contract hires to exec-level searches
- Involved in team buildouts for finance, healthcare, and tech
Services:
- Recruitment of ML and AI professionals
- Contract staffing for machine learning teams
- Executive search for data leadership roles
- Talent advisory for data team growth
Contact Information:
- Website: www.harnham.com
- E-mail: info@harnham.com
- Twitter: x.com/harnhamdata
- LinkedIn: www.linkedin.com/company/harnham
- Instagram: www.instagram.com/harnhamlife
- Address: Herengracht 124-128, 1015 BT Amsterdam, Netherlands
- Phone: +31 20 369 0617
Conclusion
Machine learning isn’t waiting on some big wave to hit – it’s already here, built into logistics workflows, credit risk engines, ad platforms, health diagnostics, and probably the app you used this morning. Across Europe, the ML scene isn’t defined by a single trend or stack – it’s a patchwork of infrastructure-first builds, tightly scoped PoCs, and long-haul transformation projects.
What really sets companies apart now isn’t whether ML is used – it’s how it’s embedded. Some teams treat it like a lab experiment. Others bake it into the core: tools, workflows, even the way decisions are made day to day. The companies listed here fall into that second group. The focus isn’t on buzzwords or pitch decks – it’s on shipping usable systems, keeping them healthy post-launch, and evolving them once real data starts flowing. Not every ML model survives contact with production. These teams are built around making sure it does.
