Addepto vs N-iX: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of N-iX (4.4/5) 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.. N-iX is the stronger option for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery.. The right choice depends on your project size, budget, and required tech stack.
Addepto vs N-iX: head-to-head summary
| Criterion | Addepto | N-iX |
|---|---|---|
| Founded | 2018 | 2002 |
| HQ | Warsaw, Poland | Lviv, Ukraine (registered HQ: Valletta, Malta) |
| Team size | 51–200 | 1,001–5,000 |
| Rating | 4.4 / 5 | 4.4 / 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. | Enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery. |
| Pricing model | Project-based | Time & Material, Fixed project |
| Min. engagement | $10,000 | $100,000+ |
| Primary tech stack | Python, MLOps tooling, Cloud ML platforms (AWS/GCP/Azure) | AWS, Microsoft Azure, Google Cloud |
| Industries served | Finance, Healthcare, Retail | Automotive, Telecom, Manufacturing, Transportation |
Addepto vs N-iX: 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.
N-iX
N-iX began as Novellix in 2002, building product applications for Novell's Linux platform out of Lviv, Ukraine, and has since grown into a broader software engineering company with a corporate registration in Malta and delivery hubs across Ukraine, Poland, Sweden, and beyond. The company reports more than 2,400 engineers company-wide and states it holds over 350 active cloud certifications across Microsoft, AWS, Google Cloud, Palantir, SAP, and Snowflake. Its dedicated data and AI practice covers machine learning, MLOps, generative AI consulting, and data warehouse/lake architecture, with publicly named enterprise clients including Bosch, Siemens, AutoScout24, and Lebara.
Services and capabilities: Addepto vs N-iX
| Capability | Addepto | N-iX |
|---|---|---|
| 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 N-iX
| Framework / platform | Addepto | N-iX |
|---|---|---|
| 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 | ✓ |
| Microsoft Azure | N/A | ✓ |
| Kubernetes | N/A | ✓ |
| Snowflake | N/A | ✓ |
| NVIDIA | N/A | N/A |
Pricing comparison: Addepto vs N-iX
| Criterion | Addepto | N-iX |
|---|---|---|
| Minimum engagement | $10,000 | $100,000+ |
| Engagement models | Fixed project, Advisory/consulting retainer | Time & Material, Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Enterprise |
Target audience comparison: Addepto vs N-iX
| Dimension | Addepto | N-iX |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Finance, Healthcare, Retail | Automotive, Telecom, Manufacturing |
| Best use cases | Auditing an existing ML pipeline and recommending MLOps improvements, Running a well-scoped, budget-constrained machine learning pilot | Building an enterprise-scale data lake or warehouse to feed downstream ML models, Running a large, multi-workstream MLOps implementation across several business units |
| Typical project type | Fixed project | Time & Material |
Addepto vs N-iX: 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. |
| N-iX | |
|---|---|
| + | Clutch rating of 4.8/5 across 35 verified reviews. |
| + | Named, verifiable enterprise clients including Bosch, Siemens, and AutoScout24. |
| + | Broadest multi-cloud certification depth (350+) among the companies researched for this list. |
| + | Maintained delivery continuity through significant regional disruption, per company and press reporting. |
| - | High minimum engagement ($100K+) excludes smaller buyers and early-stage startups. |
| - | Legal HQ (Malta) differs from primary engineering hub (Ukraine), which buyers should clarify during contracting. |
| - | As a multi-service engineering firm, ML/AI competes with several other practice areas for account attention. |
| - | Company-wide headcount (2,400+) makes it harder to gauge the actual size of the ML-specific delivery 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 N-iX?
N-iX is the right choice for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery..
Broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice.. Minimum engagement starts at $100,000+. Works best with clients in Automotive, Telecom, Manufacturing, Transportation.
Decision matrix: Addepto vs N-iX
| 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 | N-iX |
| Your budget is at the lower end | Addepto |
| You need specialist depth in a specific vertical | N-iX |
| 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 N-iX
| Use case | Addepto fit | N-iX 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 |
| Building an enterprise-scale data lake or warehouse to feed downstream ML models | Limited | Strong | N-iX |
| Running a large, multi-workstream MLOps implementation across several business units | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Strong | Both equally |
Verdict: Addepto vs N-iX
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..
N-iX (4.4/5) is the better choice when enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery.. If your situation matches those criteria, N-iX is a competitive option.
Related comparisons
Addepto vs N-iX FAQ
Is Addepto better than N-iX?
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.. N-iX is better for enterprise buyers wanting a large, heavily certified engineering partner for combined data platform and ML delivery..
How do Addepto and N-iX differ in pricing?
Addepto uses project-based pricing with a minimum engagement of $10,000. N-iX uses time & material, fixed project pricing with a minimum engagement of $100,000+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or N-iX?
N-iX 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 N-iX?
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.. N-iX's primary differentiator is: broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice.. They also differ in team size (51–200 vs 1,001–5,000), minimum engagement ($10,000 vs $100,000+), and primary industries served (Finance, Healthcare vs Automotive, Telecom).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.