N-iX vs Addepto: full comparison for 2026
Quick verdict
N-iX (4.1/5) edges ahead of Addepto (3.9/5) overall. N-iX is the better choice for Manufacturing, IoT, retail enterprises — ML plus hardware integration. Addepto is the stronger option for Manufacturing, logistics, retail SMEs — focused boutique, senior access. The right choice depends on your project size, budget, and required tech stack.
N-iX vs Addepto: head-to-head summary
| Criterion | N-iX | Addepto |
|---|---|---|
| Founded | 2002 | 2017 |
| HQ | Malta / Lviv, Ukraine | Warsaw, Poland |
| Team size | 2,400+ | 50–100 |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Named enterprise clients (Bosch, Siemens, eBay) across manufacturing and retail with 2,400+ engineers spanning software, embedded systems, and cloud ML | Focused vertical expertise in manufacturing predictive maintenance and retail AI at boutique scale — avoids the generalist overhead of larger firms for targeted use cases |
| Pricing model | Dedicated team, T&M | Fixed project, T&M |
| Min. engagement | $50K | $15K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | Manufacturing, Retail / E-commerce, Financial Services, Logistics, Technology / SaaS | Manufacturing, Retail / E-commerce, Financial Services, Logistics |
N-iX vs Addepto: overview
N-iX
N-iX was founded in 2002 and is headquartered in Malta, with operations across Poland (Kraków, Warsaw, Wrocław), Ukraine (Lviv, Kyiv), Bulgaria, Romania, India, and the Americas. The company employs over 2,400 professionals and helps more than 160 organisations worldwide, including Bosch, Siemens, eBay, and Questrade. Its AI and ML practice covers computer vision, NLP, agentic AI, and data engineering within a broader software engineering capability set. N-iX is particularly strong in manufacturing IoT-connected ML, embedded AI, and enterprise data platform modernisation, segments where its hardware-software engineering combination is a genuine differentiator.
Addepto
Addepto is a machine learning and AI consultancy established in 2017 and headquartered in Warsaw, Poland, with approximately 52 employees. Despite its small size, Addepto has built a focused portfolio in manufacturing predictive maintenance, logistics AI, and retail recommendation engines, delivering scalable ML solutions that align with the specific data patterns and operational constraints of each vertical. The firm's notable projects include predictive maintenance implementations for manufacturing clients, logistics optimisation using AI-driven analysis, and recommendation engines for retail. Addepto is one of the more accessible boutiques by team size and minimum engagement, suitable for companies requiring a specialised ML partner without enterprise-level overhead.
Services and capabilities: N-iX vs Addepto
| Capability | N-iX | Addepto |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Deep learning | ✗ | ✗ |
| NLP / Text analytics | ✓ | ✓ |
| Computer vision | ✓ | ✓ |
| MLOps & deployment | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| AI strategy | ✓ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Fixed-price projects | ✗ | ✓ |
| Dedicated team model | ✓ | ✗ |
Tech stack comparison: N-iX vs Addepto
| Framework / platform | N-iX | Addepto |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Kubernetes | ✓ | ✓ |
| Databricks | N/A | N/A |
| MLflow | N/A | ✓ |
Pricing comparison: N-iX vs Addepto
| Criterion | N-iX | Addepto |
|---|---|---|
| Minimum engagement | $50K | $15K |
| Engagement models | Dedicated team, Time & materials | Fixed project, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: N-iX vs Addepto
| Dimension | N-iX | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail / E-commerce, Financial Services | Manufacturing, Retail / E-commerce, Financial Services |
| Best use cases | Computer vision systems for manufacturing quality control integrated with production line IoT sensors, ML-driven predictive maintenance for industrial equipment with embedded sensor data pipelines | Predictive maintenance ML for manufacturing equipment with IoT sensor data integration, Recommendation engine development for e-commerce and retail personalisation platforms |
| Typical project type | Dedicated team | Fixed project |
N-iX vs Addepto: pros and cons
| N-iX | |
|---|---|
| + | Named enterprise clients including Bosch, Siemens, and eBay verify delivery across both manufacturing and retail domains |
| + | Rare combination of software engineering, embedded systems, and cloud ML under one team for industrial IoT clients |
| + | 2,400+ professional team provides depth for complex concurrent programmes |
| + | Multi-country delivery footprint with European Union regulatory alignment for compliance-sensitive projects |
| + | Over two decades of operation provides supply chain, process, and quality management maturity |
| - | AI/ML is one practice within a broader software engineering portfolio — specialist ML depth is thinner than dedicated boutiques |
| - | Ukraine-centric delivery centres carry geopolitical risk; assess redundancy and contingency with N-iX before committing |
| - | Less suitable for pure data science or research-oriented ML engagements compared to analytics-first firms |
| Addepto | |
|---|---|
| + | Focused manufacturing and retail portfolio reduces onboarding time on predictive maintenance and recommendation system projects |
| + | Small team ensures senior practitioner involvement throughout the engagement rather than junior staffing after kickoff |
| + | Competitive Warsaw-based rates are well below US boutiques of equivalent vertical ML depth |
| + | Accessible $15K minimum allows SMEs to engage professional ML delivery without enterprise investment levels |
| - | Team of ~52 strictly limits concurrent capacity — unsuitable for clients needing multiple simultaneous ML tracks |
| - | Founded 2017 — shorter track record than established competitors for high-stakes procurement decisions |
| - | Narrow vertical focus means less applicable experience for clients in healthcare, financial services, or media |
| - | Less infrastructure in generative AI, agentic systems, or large-scale MLOps compared to larger firms |
Who should choose N-iX?
A typical fit: computer vision systems for manufacturing quality control integrated with production line IoT sensors.
Named enterprise clients (Bosch, Siemens, eBay) across manufacturing and retail with 2,400+ engineers spanning software, embedded systems, and cloud ML. Minimum engagement starts at $50K. Works best with clients in Manufacturing, Retail / E-commerce, Financial Services, Logistics, Technology / SaaS.
Who should choose Addepto?
A typical fit: predictive maintenance ML for manufacturing equipment with IoT sensor data integration.
Focused vertical expertise in manufacturing predictive maintenance and retail AI at boutique scale — avoids the generalist overhead of larger firms for targeted use cases. Minimum engagement starts at $15K. Works best with clients in Manufacturing, Retail / E-commerce, Financial Services, Logistics.
Decision matrix: N-iX vs Addepto
| 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 | Both may offer discovery engagements |
Use case fit: N-iX vs Addepto
| Use case | N-iX fit | Addepto fit | Winner |
|---|---|---|---|
| Computer vision systems for manufacturing quality control integrated with production line IoT sensors | Strong | Limited | N-iX |
| ML-driven predictive maintenance for industrial equipment with embedded sensor data pipelines | Strong | Limited | N-iX |
| Predictive maintenance ML for manufacturing equipment with IoT sensor data integration | Strong | Strong | Both equally |
| Recommendation engine development for e-commerce and retail personalisation platforms | Limited | Strong | Addepto |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: N-iX vs Addepto
N-iX (4.1/5) is the stronger overall choice for most Machine Learning projects. Named enterprise clients (Bosch, Siemens, eBay) across manufacturing and retail with 2,400+ engineers spanning software, embedded systems, and cloud ML.
Addepto (3.9/5) is worth a look if you need recommendation engine development for e-commerce and retail personalisation platforms. If your situation matches that, Addepto is a competitive option.
Related comparisons
N-iX vs Addepto FAQ
Is N-iX better than Addepto?
N-iX (4.1/5) scores higher overall, but "better" depends on your use case. N-iX's strongest advantage: named enterprise clients including Bosch, Siemens, and eBay verify delivery across both manufacturing and retail domains. Addepto's strongest advantage: focused manufacturing and retail portfolio reduces onboarding time on predictive maintenance and recommendation system projects.
How do N-iX and Addepto differ in pricing?
N-iX uses dedicated team, t&m pricing with a minimum engagement of $50K. Addepto uses fixed project, t&m pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: N-iX or Addepto?
Addepto is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between N-iX and Addepto?
N-iX's primary differentiator is: named enterprise clients (Bosch, Siemens, eBay) across manufacturing and retail with 2,400+ engineers spanning software, embedded systems, and cloud ML. Addepto's primary differentiator is: focused vertical expertise in manufacturing predictive maintenance and retail AI at boutique scale — avoids the generalist overhead of larger firms for targeted use cases. They also differ in team size (2,400+ vs 50–100), minimum engagement ($50K vs $15K), and primary industries served (Manufacturing, Retail / E-commerce vs Manufacturing, Retail / E-commerce).