Predictive analytics isn’t about dashboards and buzzwords anymore – it’s about whether your systems can actually respond before things go sideways. Across Europe, a growing number of companies are building serious capability in this space. They’re not just feeding you models – they’re helping teams make real decisions from live data, patterns, and signals. Whether it’s supply chain, finance, health, or logistics, the firms on this list are in the trenches helping businesses see what’s coming – and act on it before it’s too late.
1. A-listware
A-listware provides predictive analytics services across Europe, helping companies turn raw data into decisions that actually stick. Our work spans multiple industries – healthcare, retail, logistics, finance – and we approach each engagement with a focus on structure, clarity, and long-term usability. Whether we’re working with historical data or setting up real-time prediction models, we always align with the operational needs of the client, not just the technical ones.
We don’t just build models – we build systems that plug into workflows and stay relevant over time. Forecasting patient workloads, predicting inventory demand, optimizing shift schedules, or helping a client understand customer behavior – all of it requires data engineering that holds up under real conditions. Our teams work closely with stakeholders to make sure insights are clear, usable, and linked to actual outcomes.
Key Highlights:
- Predictive analytics services provided across all of Europe
- Structured onboarding with clearly defined goals and risk planning
- Domain knowledge across more than 30 verticals, including healthcare and logistics
- Ongoing support for infrastructure, modeling, and result interpretation
- Dedicated data teams with access to a large internal candidate pool
- Low attrition, stable delivery, and clear escalation paths
Services:
- Predictive analytics for healthcare, retail, finance, and logistics
- Machine learning model design and implementation
- Forecasting and trend analysis (demand, risk, customer behavior)
- Data engineering and pipeline management
- Real-time and batch data processing setups
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. IntelliSoft
IntelliSoft works with businesses that need to bring structure and foresight to their data. They focus on helping companies move from scattered datasets to operational insights through predictive modeling, reporting, and machine learning setups. Most of their work starts by identifying gaps in existing systems and then layering on analytics workflows that can be managed internally or supported externally.
They tend to work across healthcare, logistics, marketing tech, education, and IoT, where visibility into performance and customer behavior is essential. In practice, this means combining data mining, quality assessment, and big data processing into repeatable pipelines that feed visual dashboards and models.
Key Highlights:
- Works with clients across Europe in healthcare, MarTech, logistics, and more
- Offers predictive analytics combined with data quality improvements
- Supports integration into existing systems or platforms
- Provides engagement models including staff augmentation and dedicated teams
- Delivers reports, dashboards, and machine learning models
Services:
- Predictive analytics for customer behavior and trend analysis
- Data mining and feature extraction from structured/unstructured sources
- Business intelligence dashboard and KPI reporting setup
- Data quality review and enhancement
- Visualization tools integration (Power BI, Tableau)
- Data architecture and big data frameworks (Spark, Hadoop)
- Model retraining and post-deployment analytics support
Contact Information:
- Website: intellisoft.io
- E-mail: swiss@intellisoftware.net
- Address: Bernstrasse 15, 8952 Schlieren, Switzerland
3. Intellias
Intellias helps companies rework their internal data management processes, especially when dealing with multiple data sources or fragmented reporting. A lot of their analytics work sits on top of infrastructure rebuilds or larger modernization efforts, where the end goal is consistent, automated insight delivery.
Their projects often include the setup of full data platforms with pipelines, storage, and visualization. Predictive components are usually tied to specific business cases, like segmenting customer behavior or anticipating risk. Their work in financial services and lending has focused on decision automation, operational reporting, and custom dashboards built around Microsoft Azure tools.
Key Highlights:
- Strong focus on financial services and regulated environments
- Delivers full-stack data platforms, not just analytics layers
- Combines warehousing, BI reporting, and predictive segmentation
- Commonly integrates Microsoft Azure toolsets
- Works across multiple European markets
Services:
- Predictive analytics integrated into BI dashboards
- Data warehouse architecture and setup
- Azure Data Factory and SQL-based data pipelines
- Self-service analytics platform deployment
- CRM and call center data integration for customer insight
- Automated customer segmentation using ML models
Contact Information:
- Website: intellias.com
- E-mail: security@intellias.com
- Facebook: www.facebook.com/Intellias.GlobalPage
- LinkedIn: www.linkedin.com/company/intellias
- Instagram: www.instagram.com/intellias_global
- Address: Wilhelm-Wagenfeld-Str. 28, 80807, 4th floor, Munich, Germany
- Phone: +49 8001800992
4. Inoxoft
Inoxoft supports companies that need predictive analytics to guide product, pricing, or operations decisions. Their services are built around breaking large, unstructured datasets into usable formats, then running models to find trends and forecasts. Whether it’s in healthcare, education, logistics, or fintech, the focus is on automating the decision-making process with custom tools that slot into existing platforms.
Their delivery model covers the full cycle: from data ingestion to deployment, with emphasis on transforming operational bottlenecks into smoother, data-backed workflows. They also bring visual tooling and scenario modeling into play, especially for clients who want to test ideas before rolling them into production.
Key Highlights:
- Experience with predictive analytics across multiple industries
- Covers full workflow from data ingestion to deployment
- Works with both structured and visual data (e.g., image recognition)
- Combines business logic with advanced analytics tools
- Offers collaboration models including team extension
Services:
- Predictive analytics for forecasting, risk analysis, and planning
- Sales prediction and demand modeling
- Pricing strategy support using market data
- Marketing optimization and A/B testing analysis
- Visual data processing (e.g., image-based pattern recognition)
Contact Information:
- Website: inoxoft.com
- E-mail: contact@inoxoft.com
- Facebook: www.facebook.com/inoxoft
- Twitter: x.com/InoXoft_Inc
- LinkedIn: www.linkedin.com/company/inoxoft
- Instagram: www.instagram.com/inoxoft_team
- Address: Muchoborska 8, budynek b1, 1 pietro, Wrocław, 54-424
- Phone: (267) 310-2646
5. Aress
Aress delivers predictive analytics as part of a broader data-focused services portfolio. Their work centers on solving tangible business problems, with models built around forecasting, anomaly detection, and customer behavior analysis. Most of what they do starts with clear objectives and ties directly into how the client makes operational decisions.
They often operate as an extension of the client’s team, supporting areas like churn prediction, demand forecasting, and fraud detection. Much of their predictive work draws from historical datasets and blends structured and unstructured sources, especially in sectors like healthcare and ecommerce. Aress doesn’t stop at the model – they help clients embed it into day-to-day operations and keep it updated as things evolve.
Key Highlights:
- Accustomed to working with both structured and unstructured data
- Focus on operational use cases like sales, maintenance, and churn
- Offers full lifecycle support from modeling to ongoing model retraining
- Models designed to integrate into business decision processes
- Supports regulatory-heavy industries with secure implementation
Services:
- Predictive modeling with historical data
- Anomaly detection and risk analytics
- Text analytics for social and customer sentiment
- Custom forecasting solutions
Contact Information:
- Website: www.aress.com
- E-mail: info@aress.com
- Facebook: www.facebook.com/AressSoftware
- Twitter: x.com/aress_software
- LinkedIn: www.linkedin.com/company/aress-software
- Address: Peter House, Oxford Street, Manchester, M1 5AN
- Phone: +44 (0) 7446 87 37 97
6. Beetroot
Beetroot provides predictive analytics services through both team extension and turnkey project models. Most of their work starts with helping clients clean up data pipelines and assess infrastructure readiness before diving into model design. They’re strong on the engineering side – setting up cloud environments, tuning pipelines, and automating model training – but also cover the consultative layer around feasibility, model selection, and outcomes planning.
They support a wide spread of use cases, from marketing optimization and churn prevention to real-time demand forecasting. Rather than relying on off-the-shelf solutions, Beetroot tends to build tailored models or extend existing tools with custom logic. They also offer predictive analytics workshops, which are popular with teams rolling out analytics across departments and need internal upskilling alongside delivery.
Key Highlights:
- Supports both project-based work and embedded team models
- Hands-on with data pipeline development and cloud deployment
- Combines predictive analytics with NLP for text-heavy data
- Helps clients plan for infrastructure scaling and long-term maintenance
- Offers custom training to build internal capabilities
Services:
- Custom predictive model development
- Churn and retention analysis
- Marketing and sales forecasting
- Time-series and inventory forecasting
Contact Information:
- Website: beetroot.co
- E-mail: hello@beetroot.se
- Facebook: www.facebook.com/beetroot.se
- LinkedIn: www.linkedin.com/company/beetroot-se
- Instagram: www.instagram.com/beetroot.se
- Address: 116 30 Stockholm, Sweden, Beetroot AB
- Phone: +46705188822
7. InData Labs
InData Labs focuses on predictive analytics through the lens of applied AI and machine learning. Their work is typically project-driven, with custom solutions built for specific scenarios like credit scoring, customer segmentation, or dynamic pricing. Most engagements involve a blend of consulting and development, starting with problem scoping and moving through modeling, training, and deployment.
They bring together data scientists and machine learning engineers to deliver solutions that slot into real business workflows. Much of their work supports data-rich verticals like fintech, retail, and healthcare. InData Labs emphasizes model automation and scalability, so clients can iterate without rebuilding.
Key Highlights:
- Focus on business-driven predictive models across core functions
- Works across industries with ready-to-customize model templates
- Covers full project lifecycle from feasibility to production
- Uses tailored ML models instead of fixed tools
- Supports scaling and ongoing model refinement
Services:
- Predictive analytics consulting
- Custom model design and training
- Customer lifetime value prediction
- Segmentation and recommender systems
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
8. Binariks
Binariks provides predictive analytics as part of a broader data science offering, often working with clients who are building from scattered datasets toward more structured forecasting. Their typical approach combines data collection, ML model design, and integration into existing tools.
Projects tend to fall into areas like customer behavior modeling, churn prediction, risk analysis, and operational planning. Their team builds predictive models based on historical data and helps clients fine-tune outcomes through retraining and feedback loops. In practice, the focus is less on abstract algorithm performance and more on making those insights available inside business systems through visual dashboards or microservices.
Key Highlights:
- Predictive analytics built on top of data preparation and automation
- Works across sectors including healthcare, finance, and logistics
- Emphasis on long-term support and model retraining
- Combines forecasting with intelligent automation and optimization
- Helps embed models into business systems using custom microservices
Services:
- Custom ML models for forecasting and risk scoring
- Predictive analytics for customer retention and sales optimization
- Churn prediction using structured and behavioral data
- Anomaly detection and fraud risk modeling
- Scenario analysis and optimization modeling
- MLOps and lifecycle support for deployed models
Contact Information:
- Website: binariks.com
- E-mail: info@binariks.com
- Facebook: www.facebook.com/binariks
- LinkedIn: www.linkedin.com/company/binariks
- Instagram: www.instagram.com/binariks.inc
- Address: European Development, Centers, Estonia, Narva mnt 13-233, Tallinn 10151
- Phone: +3726991518
9. Alvarez & Marsal
Alvarez & Marsal uses predictive analytics mainly within corporate transactions and financial advisory work. Rather than offering standalone tech services, they apply modeling inside due diligence and post-acquisition planning. Their predictive work is tightly linked to finance – helping clients forecast profitability, detect payment issues, or assess the potential for churn across customer bases.
They work with internal company data and external sources to model trends and simulate outcomes. In mergers or buyouts, that might include estimating future cash flow or testing performance under macroeconomic shifts. Models are run through their internal platforms and tied to scenario planning, which is useful for clients looking to reduce decision bias and back investments with data.
Key Highlights:
- Predictive models embedded into due diligence and M&A strategy
- Uses financial history and macro indicators for forecasting
- Focus on revenue, churn, collectability, and post-deal scenarios
- Proprietary platform used for scenario simulation
- Clients include private equity and corporate buyers
Services:
- Forecasting revenue and profit using historical data
- Churn modeling to assess retention risks
- Payment predictability analysis
- Scenario-based planning for pre- and post-acquisition
- Macro factor correlation and cost modeling
- Dashboarding and insight reporting for internal use
Contact Information:
- Website: www.alvarezandmarsal.com
- Facebook: www.facebook.com/alvarezandmarsal
- Twitter: x.com/alvarezmarsal
- LinkedIn: www.linkedin.com/company/alvarez-&-marsal
- Instagram: www.instagram.com/alvarezandmarsal_life
- Address: Av. Diagonal 640, Planta 6, 08017 Barcelona, Spain
- Phone: +34 91 781 5521
10. Innowise
Innowise supports predictive analytics projects by helping companies move from raw data to usable forecasts. Their work spans industries like healthcare, retail, logistics, and finance, and most projects combine engineering with model development. The focus is often on forecasting trends in customer behavior, sales demand, supply chain movements, or operational bottlenecks.
Their team handles both setup and maintenance – meaning clients can build new models or bring Innowise into existing projects. Models are usually part of broader workflows that include data visualization, automation, or integration with internal systems. Where needed, they also support custom dashboard creation and maintain the models long after deployment to keep output aligned with changing conditions.
Key Highlights:
- Predictive models built for specific sectors like eCommerce and supply chain
- Offers both full-cycle delivery and targeted model development
- Combines analytics with ongoing model optimization and support
- Experience in forecasting, segmentation, and scenario testing
- Works with structured, behavioral, and transactional data
Services:
- Forecasting models for demand planning and inventory
- Customer segmentation and scoring
- Predictive maintenance and resource planning
- Visual dashboards to track model output
- Custom ML solutions and data science consulting
Contact Information:
- Website: innowise.com
- E-mail: contact@innowise.com
- Twitter: x.com/innowisegroup
- LinkedIn: www.linkedin.com/company/innowise-group
- Address: Rondo Daszyńskiego 2B, The Warsaw HUB B, Warszawa
- Phone: +48 787 027 706
Conclusion
The companies featured here take very different routes into predictive analytics, but they all lean toward practical delivery over abstract innovation. Some focus on embedding models into financial planning or due diligence. Others handle the entire data pipeline, from messy source inputs to production-ready forecasts. What matters is that each group treats prediction not as a standalone capability, but as something that needs to sit inside a broader system – one that makes decisions, allocates resources, or adjusts in real time.
If there’s a takeaway, it’s that predictive work isn’t just about algorithms. It’s about what happens after the model runs – where it shows up, who uses it, and how often it needs to be retrained. The best setups don’t chase the latest buzzwords. They keep things maintainable, grounded in real data, and flexible enough to evolve as the business does.
