ELEKS vs DataRobot: full comparison for 2026
Last updated: July 2026
Quick verdict
ELEKS (4.1/5) edges ahead of DataRobot (3.9/5) overall. ELEKS is the better choice for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. DataRobot is the stronger option for enterprises that want to standardize on a single automated ML platform and use vendor professional services for implementation and model support.. The right choice depends on your project size, budget, and required tech stack.
ELEKS vs DataRobot: head-to-head summary
| Criterion | ELEKS | DataRobot |
|---|---|---|
| Founded | 1991 | 2012 |
| HQ | Tallinn, Estonia (engineering hub: Lviv, Ukraine) | Boston, USA |
| Team size | 1,001–5,000 | 501–1,000 |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Best for | Enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor. | Enterprises that want to standardize on a single automated ML platform and use vendor professional services for implementation and model support. |
| Pricing model | Time & Material, Fixed project | Platform licensing plus professional services; not fully published |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Cloud ML platforms (AWS/Azure/GCP), Data engineering tooling | DataRobot AI Platform (proprietary), AutoML tooling, Cloud deployment (AWS/Azure/GCP) |
| Industries served | Financial services, Healthcare, Manufacturing, Insurance | Financial services, Healthcare, Insurance, Public sector |
ELEKS vs DataRobot: overview
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.
DataRobot
DataRobot was founded in 2012 by Jeremy Achin and Tom De Godoy and is headquartered in Boston, Massachusetts, with roughly 869 employees spread across six continents. The company's core product is an enterprise AI platform that automates building, deploying, and managing machine learning models, and it maintains a professional services function that supports clients through implementation, custom model development support, and platform adoption. Unlike the pure client-services firms in this comparison, DataRobot is fundamentally a software vendor whose services arm exists to support platform-based model development rather than fully bespoke, platform-independent model builds.
Services and capabilities: ELEKS vs DataRobot
| Capability | ELEKS | DataRobot |
|---|---|---|
| Custom model training | ✓ | ✓ |
| Fine-tuning & adaptation | ✗ | ✗ |
| MLOps pipeline | ✓ | ✓ |
| Model deployment & serving | ✗ | ✓ |
| Data engineering for ML | ✓ | ✗ |
| ML infrastructure management | ✗ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP & LLM development | ✗ | ✗ |
| Forecasting & time-series modeling | ✗ | ✗ |
| ML strategy consulting | ✗ | ✗ |
Tech stack comparison: ELEKS vs DataRobot
| Framework / platform | ELEKS | DataRobot |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Amazon Bedrock | N/A | N/A |
| Google Cloud | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Kubernetes | ✓ | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: ELEKS vs DataRobot
| Criterion | ELEKS | DataRobot |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Time & Material, Fixed project, Dedicated team | Platform subscription, Professional services (implementation support) |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: ELEKS vs DataRobot
| Dimension | ELEKS | DataRobot |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Financial services, Healthcare, Manufacturing | Financial services, Healthcare, Insurance |
| Best use cases | Running an enterprise-scale data science initiative alongside a broader software modernization program, Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components | Standardizing enterprise ML model development on a single automated platform with vendor support, Accelerating time-to-deployment for common predictive modeling use cases |
| Typical project type | Time & Material | Platform subscription |
ELEKS vs DataRobot: pros and cons
| ELEKS | |
|---|---|
| + | Over three decades of continuous operation, unusually long for this category. |
| + | Large engineering bench (2,000+ employees) supports substantial delivery capacity. |
| + | Data science practice is embedded within a mature enterprise software engineering organization. |
| + | Multi-region European and North American office footprint. |
| - | AI/ML is one practice area within a much broader enterprise software portfolio, not the company's primary specialization. |
| - | Specific, named ML case studies with quantified outcomes are limited in available public sources. |
| - | Pricing minimums are not published. |
| - | Long operating history does not necessarily translate into deep modern ML/LLM specialization relative to newer, AI-first boutiques. |
| DataRobot | |
|---|---|
| + | Automated ML platform can significantly speed up model development and deployment cycles for standard use cases. |
| + | Professional services team supports clients directly through platform adoption rather than leaving them to self-serve. |
| + | Global presence across six continents with a workforce spanning sales, engineering, and customer success. |
| + | Over a decade of focused operation as an enterprise AI/ML platform company. |
| - | Model development is tied to DataRobot's own platform, limiting flexibility for clients wanting a fully platform-agnostic, bespoke build. |
| - | As a software vendor first, professional services depth is generally narrower than dedicated consultancies in this list. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its services arm in available public sources. |
| - | Pricing is a mix of platform licensing and services, making total cost of ownership less transparent than pure T&M consultancies. |
Who should choose ELEKS?
ELEKS is the right choice for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..
One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades.. Minimum engagement starts at Not published. Works best with clients in Financial services, Healthcare, Manufacturing, Insurance.
Who should choose DataRobot?
DataRobot is the right choice for enterprises that want to standardize on a single automated ML platform and use vendor professional services for implementation and model support..
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.. Minimum engagement starts at Not published. Works best with clients in Financial services, Healthcare, Insurance, Public sector.
Decision matrix: ELEKS vs DataRobot
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | ELEKS |
| You need a large dedicated team for an ongoing programme | ELEKS |
| Your budget is at the lower end | Compare: ELEKS (Not published) vs DataRobot (Not published) |
| You need specialist depth in a specific vertical | ELEKS |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: ELEKS vs DataRobot
| Use case | ELEKS fit | DataRobot fit | Winner |
|---|---|---|---|
| Running an enterprise-scale data science initiative alongside a broader software modernization program | Strong | Limited | ELEKS |
| Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components | Strong | Limited | ELEKS |
| Standardizing enterprise ML model development on a single automated platform with vendor support | Limited | Strong | DataRobot |
| Accelerating time-to-deployment for common predictive modeling use cases | Limited | Strong | DataRobot |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Limited | Limited | Both equally |
Verdict: ELEKS vs DataRobot
ELEKS (4.1/5) is the stronger overall choice for most ML Model Development projects. One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades.. It is best for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..
DataRobot (3.9/5) is the better choice when enterprises that want to standardize on a single automated ML platform and use vendor professional services for implementation and model support.. If your situation matches those criteria, DataRobot is a competitive option.
Related comparisons
ELEKS vs DataRobot FAQ
Is ELEKS better than DataRobot?
ELEKS (4.1/5) scores higher overall, but "better" depends on your use case. ELEKS is better for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. DataRobot is better for enterprises that want to standardize on a single automated ML platform and use vendor professional services for implementation and model support..
How do ELEKS and DataRobot differ in pricing?
ELEKS uses time & material, fixed project pricing with a minimum engagement of Not published. DataRobot uses platform licensing plus professional services; not fully published pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: ELEKS or DataRobot?
ELEKS is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between ELEKS and DataRobot?
ELEKS's primary differentiator is: one of the longest operating histories (since 1991) among firms researched for this list, predating the ai consulting boom by decades.. DataRobot's primary differentiator is: 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.. They also differ in team size (1,001–5,000 vs 501–1,000), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Healthcare vs Financial services, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.