Addepto vs DataRobot: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of DataRobot (3.9/5) overall. Addepto is the better choice for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build.. 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.
Addepto vs DataRobot: head-to-head summary
| Criterion | Addepto | DataRobot |
|---|---|---|
| Founded | 2018 | 2012 |
| HQ | Warsaw, Poland | Boston, USA |
| Team size | 51–200 | 501–1,000 |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Best for | Cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build. | Enterprises that want to standardize on a single automated ML platform and use vendor professional services for implementation and model support. |
| Pricing model | Project-based | Platform licensing plus professional services; not fully published |
| Min. engagement | $10,000 | Not published |
| Primary tech stack | Python, MLOps tooling, Cloud ML platforms (AWS/GCP/Azure) | DataRobot AI Platform (proprietary), AutoML tooling, Cloud deployment (AWS/Azure/GCP) |
| Industries served | Finance, Healthcare, Retail | Financial services, Healthcare, Insurance, Public sector |
Addepto vs DataRobot: overview
Addepto
Addepto is a Poland-based AI consulting firm founded in 2018 by Artur Haponik and Edwin Lisowski that focuses specifically on machine learning consulting, MLOps consulting, and data/analytics advisory work rather than broader software development. The company has around 52 employees and holds a 4.7 Clutch rating, with Clutch-reported project costs typically in the $10,000–$49,000 range, making it one of the more budget-accessible options among firms in this category. Addepto has been recognized among Forbes' top AI consulting companies and appeared on the Deloitte Technology Fast 500 EMEA list, citing 1,193 percent revenue growth over the qualifying period. In December 2025, Addepto was acquired by KMS Technology, a US-based digital engineering, data, and AI company backed by growth private equity firm Sunstone Partners; Addepto now operates as an integrated division rather than as a fully independent company.
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: Addepto vs DataRobot
| Capability | Addepto | 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: Addepto vs DataRobot
| Framework / platform | Addepto | 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 | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: Addepto vs DataRobot
| Criterion | Addepto | DataRobot |
|---|---|---|
| Minimum engagement | $10,000 | Not published |
| Engagement models | Fixed project, Advisory/consulting retainer | Platform subscription, Professional services (implementation support) |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Addepto vs DataRobot
| Dimension | Addepto | DataRobot |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Finance, Healthcare, Retail | Financial services, Healthcare, Insurance |
| Best use cases | Auditing an existing ML pipeline and recommending MLOps improvements, Running a well-scoped, budget-constrained machine learning pilot | 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 | Fixed project | Platform subscription |
Addepto vs DataRobot: pros and cons
| Addepto | |
|---|---|
| + | 4.7 Clutch rating with lower typical project cost ($10K–$49K) than most peers in this comparison. |
| + | Named a top 10 AI consulting company by Forbes. |
| + | Deloitte Technology Fast 500 EMEA recognition (#143) signals strong recent revenue growth. |
| + | Focused specifically on ML/MLOps consulting rather than diluting attention across general software development. |
| - | Small team (~52 employees) caps capacity for large or multiple concurrent enterprise engagements. |
| - | Lower typical project size may signal a fit for smaller-scope work rather than large production ML platforms. |
| - | Public case studies with named enterprise clients are limited in available sources. |
| - | Now part of KMS Technology following the December 2025 acquisition, introducing near-term integration and roadmap uncertainty for prospective clients. |
| 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 Addepto?
Addepto is the right choice for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build..
Dedicated MLOps-consulting service line and Clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option.. Minimum engagement starts at $10,000. Works best with clients in Finance, Healthcare, Retail.
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: Addepto vs DataRobot
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Addepto |
| You need a large dedicated team for an ongoing programme | Check each company's engagement model |
| Your budget is at the lower end | Compare: Addepto ($10,000) vs DataRobot (Not published) |
| You need specialist depth in a specific vertical | DataRobot |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Addepto |
Use case fit: Addepto vs DataRobot
| Use case | Addepto fit | DataRobot fit | Winner |
|---|---|---|---|
| Auditing an existing ML pipeline and recommending MLOps improvements | Strong | Limited | Addepto |
| Running a well-scoped, budget-constrained machine learning pilot | Strong | Limited | Addepto |
| 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 | Strong | Limited | Addepto |
Verdict: Addepto vs DataRobot
Addepto (4.4/5) is the stronger overall choice for most ML Model Development projects. Dedicated MLOps-consulting service line and Clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option.. It is best for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build..
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
Addepto vs DataRobot FAQ
Is Addepto better than DataRobot?
Addepto (4.4/5) scores higher overall, but "better" depends on your use case. Addepto is better for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build.. 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 Addepto and DataRobot differ in pricing?
Addepto uses project-based pricing with a minimum engagement of $10,000. 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: Addepto or DataRobot?
DataRobot 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 Addepto and DataRobot?
Addepto's primary differentiator is: dedicated mlops-consulting service line and clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option.. 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 (51–200 vs 501–1,000), minimum engagement ($10,000 vs Not published), and primary industries served (Finance, Healthcare vs Financial services, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.