ELEKS
European software engineering company founded in 1991 with a dedicated data science practice.
Founded 1991 | Tallinn, Estonia (engineering hub: Lviv, Ukraine) | 1,001–5,000 employees | Last updated: July 2026
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What is ELEKS?
ELEKS is a long-running European software engineering company founded in 1991, with corporate presence in Tallinn, Estonia and its largest engineering hub in Lviv, Ukraine, alongside additional offices across Europe and North America. The company reports more than 2,000 employees and operates a dedicated data science and AI practice layered onto its broader enterprise software engineering services. Its history predates the modern AI/ML consulting wave by roughly three decades, giving it an unusually long operating track record compared to most peers in this list.
ELEKS was founded in 1991 and is headquartered in Tallinn, Estonia (engineering hub: Lviv, Ukraine). The firm employs 1,001–5,000 people and works primarily with clients in Financial services, Healthcare, Manufacturing, Insurance sectors. Its primary differentiator is: One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades..
ELEKS tech stack and services
PythonCloud ML platforms (AWS/Azure/GCP)Data engineering toolingKubernetes
| Service area | Details |
|---|---|
| Running an enterprise-scale data science initiative alongside a broader software modernization program | Available for Financial services, Healthcare, Manufacturing, Insurance clients |
| Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components | Available for Financial services, Healthcare, Manufacturing, Insurance clients |
| Building ML capability into an existing large enterprise software system | Available for Financial services, Healthcare, Manufacturing, Insurance clients |
| Combining data engineering and model development within one established European vendor | Available for Financial services, Healthcare, Manufacturing, Insurance clients |
ELEKS use cases
Short answer: ELEKS is best suited for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..
| Use case | Industries | Approach |
|---|---|---|
| Running an enterprise-scale data science initiative alongside a broader software modernization program | Financial services, Healthcare | Python, Cloud ML platforms (AWS/Azure/GCP) |
| Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components | Financial services, Healthcare | Python, Cloud ML platforms (AWS/Azure/GCP) |
| Building ML capability into an existing large enterprise software system | Financial services, Healthcare | Python, Cloud ML platforms (AWS/Azure/GCP) |
| Combining data engineering and model development within one established European vendor | Financial services, Healthcare | Python, Cloud ML platforms (AWS/Azure/GCP) |
ELEKS pricing
Short answer: ELEKS uses a time & material, fixed project pricing approach. Minimum engagement starts at Not published.
| Engagement model | Typical range | Best for |
|---|---|---|
| Time & Material | Variable; depends on team size | Large programmes or team augmentation |
| Fixed project | From Not published | Well-defined scope |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
ELEKS does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
ELEKS pros and cons
| Advantages | Things to consider |
|---|---|
| +Over three decades of continuous operation, unusually long for this category. | -AI/ML is one practice area within a much broader enterprise software portfolio, not the company's primary specialization. |
| +Large engineering bench (2,000+ employees) supports substantial delivery capacity. | -Specific, named ML case studies with quantified outcomes are limited in available public sources. |
| +Data science practice is embedded within a mature enterprise software engineering organization. | -Pricing minimums are not published. |
| +Multi-region European and North American office footprint. | -Long operating history does not necessarily translate into deep modern ML/LLM specialization relative to newer, AI-first boutiques. |
ELEKS vs alternatives
How ELEKS compares to the other top ML Model Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Mid-market fintech, supply chain, and SaaS companies that... | Combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in. | 4.8 | Full comparison |
| Neurons Lab | Financial services firms wanting a boutique, engineering-led partner... | End-to-end delivery model from use-case scoping to continuous production support, with declared depth in financial services. | 4.6 | Full comparison |
| DataRoot Labs | Startups and mid-market companies wanting a senior, AI-only... | Has never diversified beyond AI/ML services, and backs its delivery bench with an in-house ML training program (DataRoot University). | 4.6 | Full comparison |
| Miquido | Companies that need ML/computer-vision capability bundled with broader... | Combines a large, review-verified product engineering practice with a dedicated AI/ML/CV specialization, useful for teams needing both app and model work from one vendor. | 4.6 | Full comparison |
| Provectus | Mid-market companies that need cloud data infrastructure and... | Grew out of cloud and big-data engineering roots, giving it particular strength in the data infrastructure layer underneath ML models, not just the models themselves. | 4.5 | Full comparison |
| Neoteric | Organizations wanting a structured feasibility/strategy phase before committing... | Two-decade operating history combined with a formal upfront feasibility-assessment stage before any model-building work begins. | 4.5 | Full comparison |
| Addepto | Cost-conscious teams that specifically need MLOps consulting or... | Dedicated MLOps-consulting service line and Clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option. | 4.4 | Full comparison |
| N-iX | Enterprise buyers wanting a large, heavily certified engineering... | Broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice. | 4.4 | Full comparison |
| InData Labs | Companies needing a focused predictive-analytics or computer-vision model... | Publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims. | 4.3 | Full comparison |
| MobiDev | Small and mid-sized companies wanting a dedicated ML/data-science... | Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model. | 4.3 | Full comparison |
| Sciforce | Companies needing a research-oriented boutique for NLP, digital... | R&D-first culture with named specializations in digital signal processing and NLP that are less commonly offered as distinct practice areas by peers. | 4.2 | Full comparison |
| Sigmoid | Enterprises whose primary bottleneck is data infrastructure and... | Data-engineering-first approach with 950+ multi-cloud certified engineers, positioning it as an infrastructure specialist that also delivers ML rather than the reverse. | 4.2 | Full comparison |
| Tredence | Enterprises needing vertical-specific analytics and ML applied to... | Venture-backed growth trajectory ($205M raised) with named specialization in supply chain and customer analytics rather than generic horizontal AI consulting. | 4.2 | Full comparison |
| Quantiphi | Enterprises standardized on AWS wanting a partner with... | Deepest AWS-specific partnership credentials among firms researched, including AWS GenAI Innovation Center preferred-partner status. | 4.2 | Full comparison |
| Sigma Software Group | Companies wanting a large, diversified engineering group with... | Snowflake AI Data Cloud partnership combined with unusually broad industry diversification (AdTech through aviation to gaming). | 4.1 | Full comparison |
| Intellectsoft | Companies wanting an enterprise-name client roster and a... | Unusually strong roster of large, publicly named enterprise clients (EY, Qualcomm, London Stock Exchange) for a company of its relatively modest team size. | 4.1 | Full comparison |
| Fractal Analytics | Large enterprises wanting a scaled analytics and AI... | Maintains a dedicated internal foundational AI research team alongside client delivery work, and is now a publicly listed company (NSE/BSE) rather than privately held like most peers of similar size. | 4.1 | Full comparison |
| Xebia | Enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has... | Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone. | 4.0 | Full comparison |
| Grid Dynamics | Fortune 1000 companies wanting the financial transparency and... | The only publicly traded company (NASDAQ: GDYN) in this comparison among the mid-to-large tier, giving buyers audited financial transparency unavailable from private peers. | 4.0 | Full comparison |
| Iterate.ai | Data-sensitive enterprises (e.g., regulated industries) that require AI... | Purpose-built for on-premise/private-infrastructure AI deployment, so client data and proprietary code never leave the client's own environment. | 4.0 | Full comparison |
| Modus Create | Distributed organizations wanting a remote-first partner that pairs... | Structured AI Data Foundation assessment methodology that explicitly evaluates data readiness before committing to model development. | 4.0 | Full comparison |
| Aptus Data Labs | Companies wanting a boutique, India-based data engineering and... | Combines core data engineering consulting with specific AWS AI service implementation expertise in a boutique-sized team. | 4.0 | Full comparison |
| SoftServe | Enterprises needing edge computer vision or asset-monitoring ML... | Only company in this list simultaneously holding AWS Premier, Google Cloud AI/ML Specialization, and NVIDIA Elite Consulting Partner status, reflecting particular strength in edge and GPU-accelerated computer vision. | 4.0 | Full comparison |
| DataRobot | Enterprises that want to standardize on a single... | The only platform-first vendor in this comparison, meaning model development work happens on and around DataRobot's own automated ML software rather than being platform-agnostic. | 3.9 | Full comparison |
| Persistent Systems | Mid-market and enterprise buyers wanting a publicly traded,... | Purpose-built DxH accelerator suite for MLOps and bias detection, plus a specific Everest Group Leader ranking in the mid-market Data & AI segment rather than only the largest enterprise tier. | 3.9 | Full comparison |
| EPAM Systems | Very large enterprises wanting a publicly traded, AWS... | Proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers. | 3.9 | Full comparison |
| Globant | Large enterprises wanting industry-specific pre-packaged AI solutions ("AI... | Only company in this list organized around a formal "studio + AI Pods" delivery model, and the only one with an IDC MarketScape Worldwide Leader in AI Services designation. | 3.9 | Full comparison |
| LTIMindtree | Large enterprises, particularly in BFSI and technology/media sectors,... | Explicit ModelOps templates and model-governance/responsible-AI tooling as named, productized capabilities rather than only bespoke consulting delivery, backed by an IBM watsonx Center of Excellence. | 3.9 | Full comparison |
| Cognizant | Large enterprises, especially in healthcare, wanting a very... | Dedicated, named MLOps platform specifically built for healthcare, combined with one of the largest disclosed data/AI consultant headcounts (23,000+) in this comparison. | 3.9 | Full comparison |
| HCLTech | Very large enterprises wanting a full-stack AI vendor... | Unusually broad "chip-to-cloud" AI stack claim backed by two named proprietary platforms (Graviton for ML development, AION for AI lifecycle management), a combination not matched by most peers in this list. | 3.9 | Full comparison |
| Infosys | Very large global enterprises wanting a substantial library... | Largest disclosed library of reusable, pre-trained AI assets in this comparison (12,000+ assets, 150+ pre-trained models), positioned to accelerate delivery versus fully bespoke builds. | 3.9 | Full comparison |
| Accenture | The largest global enterprises needing AI model development... | By far the largest scale of any company in this comparison (approximately 779,000 employees, $69.67B FY2025 revenue), trading breadth and compliance maturity for less niche, hands-on model-engineering depth than boutique specialists. | 3.9 | Full comparison |
| Devbridge (a Cognizant company) | Clients who want Devbridge's original product-engineering delivery model... | The clearest ownership-change disclosure in this comparison: a formerly independent boutique now operating explicitly as a Cognizant subsidiary, combining boutique delivery heritage with large-parent-company backing. | 3.8 | Full comparison |
ELEKS FAQ
What is ELEKS?
ELEKS is a long-running European software engineering company founded in 1991, with corporate presence in Tallinn, Estonia and its largest engineering hub in Lviv, Ukraine, alongside additional offices across Europe and North America. The company reports more than 2,000 employees and operates a dedicated data science and AI practice layered onto its broader enterprise software engineering services. Its history predates the modern AI/ML consulting wave by roughly three decades, giving it an unusually long operating track record compared to most peers in this list.
How much does ELEKS charge?
ELEKS uses time & material, fixed project pricing. Minimum engagement starts at Not published. A discovery call is required to get project-specific quotes.
What tech stack does ELEKS use?
ELEKS works with Python, Cloud ML platforms (AWS/Azure/GCP), Data engineering tooling, Kubernetes. Primary industries served include Financial services, Healthcare, Manufacturing, Insurance.
Is ELEKS right for enterprise?
Enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. 1,001–5,000 team size. Key consideration: AI/ML is one practice area within a much broader enterprise software portfolio, not the company's primary specialization..
What are the best ELEKS alternatives?
The best alternatives to ELEKS depend on your use case. Top options are:
- Tensorway: combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in.
- Neurons Lab: end-to-end delivery model from use-case scoping to continuous production support, with declared depth in financial services.
- DataRoot Labs: has never diversified beyond ai/ml services, and backs its delivery bench with an in-house ml training program (dataroot university).
Compare ELEKS with other ML Model Development companies
ELEKS vs Tensorway ELEKS vs Neurons Lab ELEKS vs DataRoot Labs ELEKS vs Miquido ELEKS vs Provectus ELEKS vs Neoteric ELEKS vs Addepto ELEKS vs N-iX ELEKS vs InData Labs ELEKS vs MobiDev ELEKS vs Sciforce ELEKS vs Sigmoid ELEKS vs Tredence ELEKS vs Quantiphi ELEKS vs Sigma Software Group ELEKS vs Intellectsoft ELEKS vs Fractal Analytics ELEKS vs Xebia ELEKS vs Grid Dynamics ELEKS vs Iterate.ai ELEKS vs Modus Create ELEKS vs Aptus Data Labs ELEKS vs SoftServe ELEKS vs DataRobot ELEKS vs Persistent Systems ELEKS vs EPAM Systems ELEKS vs Globant ELEKS vs LTIMindtree ELEKS vs Cognizant ELEKS vs HCLTech ELEKS vs Infosys ELEKS vs Accenture ELEKS vs Devbridge (a Cognizant company)
Last reviewed: July 2026. Verify all details directly with ELEKS before making a decision.