Addepto vs Xebia: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of Xebia (4.0/5) 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.. Xebia is the stronger option for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Xebia: head-to-head summary
| Criterion | Addepto | Xebia |
|---|---|---|
| Founded | 2018 | 2001 |
| HQ | Warsaw, Poland | Amsterdam, Netherlands (US HQ: Atlanta, USA) |
| Team size | 51–200 | 5,001–10,000 |
| Rating | 4.4 / 5 | 4.0 / 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 wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery. |
| Pricing model | Project-based | Not published; enterprise project engagements |
| Min. engagement | $10,000 | Not published |
| Primary tech stack | Python, MLOps tooling, Cloud ML platforms (AWS/GCP/Azure) | Python, Cloud ML platforms (AWS/Azure/GCP), MLOps tooling |
| Industries served | Finance, Healthcare, Retail | Financial services, Retail, Manufacturing, Public sector |
Addepto vs Xebia: 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.
Xebia
Xebia was founded in 2001 by Rob Dielemans and Daan Teunissen in the Netherlands and has grown into a global consultancy spanning data and AI, cloud, automation, and software engineering. The Xebia Group reports between 5,000 and 10,000 employees, with corporate headquarters activity in both the Netherlands and Atlanta, Georgia. Its Data & AI Hub practice focuses on turning AI strategy into production-ready solutions, reflecting a repositioning from Xebia's original software craftsmanship and training-company roots toward an AI-first identity.
Services and capabilities: Addepto vs Xebia
| Capability | Addepto | Xebia |
|---|---|---|
| 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 Xebia
| Framework / platform | Addepto | Xebia |
|---|---|---|
| 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: Addepto vs Xebia
| Criterion | Addepto | Xebia |
|---|---|---|
| Minimum engagement | $10,000 | Not published |
| Engagement models | Fixed project, Advisory/consulting retainer | Enterprise project engagement, Dedicated team, Training/enablement |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Addepto vs Xebia
| Dimension | Addepto | Xebia |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Finance, Healthcare, Retail | Financial services, Retail, Manufacturing |
| Best use cases | Auditing an existing ML pipeline and recommending MLOps improvements, Running a well-scoped, budget-constrained machine learning pilot | Turning an existing AI strategy or pilot into a production-ready, monitored system, Combining technical training/enablement with hands-on AI model development |
| Typical project type | Fixed project | Enterprise project engagement |
Addepto vs Xebia: 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. |
| Xebia | |
|---|---|
| + | 25-year software engineering and technical training pedigree underpins its AI delivery credibility. |
| + | Large scale (5,000–10,000 employees) supports substantial enterprise program capacity. |
| + | Explicit focus on production-ready AI rather than strategy-only advisory work. |
| + | Dual US/EU headquarters presence supports transatlantic enterprise clients. |
| - | AI-first repositioning is relatively recent, so its dedicated AI/ML track record is shorter than its overall company history suggests. |
| - | No clearly located aggregate Clutch/G2 star rating in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | Large, multi-practice organization means AI/ML delivery quality may vary by regional team. |
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 Xebia?
Xebia is the right choice for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..
Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone.. Minimum engagement starts at Not published. Works best with clients in Financial services, Retail, Manufacturing, Public sector.
Decision matrix: Addepto vs Xebia
| 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 | Xebia |
| Your budget is at the lower end | Compare: Addepto ($10,000) vs Xebia (Not published) |
| You need specialist depth in a specific vertical | Xebia |
| 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 Xebia
| Use case | Addepto fit | Xebia fit | Winner |
|---|---|---|---|
| Auditing an existing ML pipeline and recommending MLOps improvements | Strong | Limited | Addepto |
| Running a well-scoped, budget-constrained machine learning pilot | Strong | Strong | Both equally |
| Turning an existing AI strategy or pilot into a production-ready, monitored system | Limited | Strong | Xebia |
| Combining technical training/enablement with hands-on AI model development | Limited | Strong | Xebia |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Limited | Addepto |
Verdict: Addepto vs Xebia
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..
Xebia (4.0/5) is the better choice when enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. If your situation matches those criteria, Xebia is a competitive option.
Related comparisons
Addepto vs Xebia FAQ
Is Addepto better than Xebia?
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.. Xebia is better for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..
How do Addepto and Xebia differ in pricing?
Addepto uses project-based pricing with a minimum engagement of $10,000. Xebia uses not published; enterprise project engagements 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 Xebia?
Xebia 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 Xebia?
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.. Xebia's primary differentiator is: quarter-century software craftsmanship and technical training heritage now applied specifically to production ai/ml delivery rather than ai strategy alone.. They also differ in team size (51–200 vs 5,001–10,000), minimum engagement ($10,000 vs Not published), and primary industries served (Finance, Healthcare vs Financial services, Retail).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.