Revelo vs N-iX: full comparison for 2026
Quick verdict
Revelo (4.0/5) edges ahead of N-iX (3.8/5) overall. Revelo is the better choice for U.S. companies that want a Latin American AI engineer without upfront fees or a long contract. N-iX is the stronger option for enterprises that want to move between augmentation and a managed team with one vendor. The right choice depends on your project size, budget, and required tech stack.
Revelo vs N-iX: head-to-head summary
| Criterion | Revelo | N-iX |
|---|---|---|
| Founded | 2014 | 2002 |
| HQ | Miami, Florida, USA | Valletta, Malta (delivery mainly in Ukraine and Poland) |
| Team size | 400,000+ network (company figure) | 2,000+ |
| Rating | 4.0 / 5 | 3.8 / 5 |
| Primary differentiator | No upfront fees, no long-term contract and published salary benchmarks | Three clearly separated engagement models with a large bench |
| Pricing model | Monthly per engineer; no upfront fees or long-term contracts (per company); senior AI/ML all-in cost about $103,000/yr (company benchmark) | Monthly per engineer or managed team; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Spark, Databricks |
| Industries served | Technology, Fintech, SaaS, Healthcare, AI labs | Financial services, Manufacturing, Retail, Telecom, Healthcare |
Revelo vs N-iX: overview
Revelo
Revelo started in 2014 (one listing says 2015) and has a U.S. base in Miami and operations in São Paulo. It places engineers from a Latin American network it puts at over 400,000, and its platform pages promise no upfront fees and no long-term contracts. Revelo also publishes salary benchmarks. Its figure for a senior AI or ML engineer is about $103,000 a year all-in, roughly 55% below a comparable U.S. hire. LLM training work made up 22% of its 2024 revenue, according to TechCrunch.
N-iX
N-iX was founded in 2002, lists its registered headquarters in Malta and delivers mostly from Ukraine, Poland and other Central European countries with more than 2,400 engineers. Its 2026 company material sets out three ways to buy: staff augmentation to extend your core team, a managed team for part of a product, or project delivery. ML and data engineers are available under all three. The firm suits enterprise procurement, though AI is a small share of its work and rates are not public.
Services and capabilities: Revelo vs N-iX
| Capability | Revelo | N-iX |
|---|---|---|
| Full-time dedicated engineers | ✓ | ✓ |
| Part-time / fractional experts | ✗ | ✗ |
| Dedicated team | ✗ | ✓ |
| Trial before commitment | ✗ | ✗ |
| Published rates | ✗ | ✗ |
| Direct hire option | ✗ | ✗ |
| Subscription or output-based pricing | ✗ | ✗ |
| Nearshore time-zone overlap | ✓ | ✗ |
| LLM / GenAI engineers | ✓ | ✗ |
| MLOps | ✗ | ✓ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✗ | ✓ |
Tech stack comparison: Revelo vs N-iX
| Framework / platform | Revelo | N-iX |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | ✓ |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | ✓ |
Pricing comparison: Revelo vs N-iX
| Criterion | Revelo | N-iX |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated, Freelance contract | Full-time dedicated, Dedicated team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Revelo vs N-iX
| Dimension | Revelo | N-iX |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Technology, Fintech, SaaS | Financial services, Manufacturing, Retail |
| Best use cases | Hiring a Brazilian ML engineer without a long contract, Budgeting a nearshore AI team from published salary data | Extending an enterprise data team, Switching an augmented team to a managed model |
| Typical project type | Full-time dedicated | Full-time dedicated |
Revelo vs N-iX: pros and cons
| Revelo | |
|---|---|
| + | No upfront fee or long-term contract |
| + | Published salary benchmarks help with budgeting |
| + | Large Latin American network on U.S. hours |
| - | Part of revenue comes from AI-lab training work |
| - | Salary figures come from Revelo itself |
| - | Founding year and headquarters differ by source |
| N-iX | |
|---|---|
| + | Clear engagement models |
| + | Large Central European bench |
| + | Long enterprise history |
| - | AI is a small part of its work |
| - | No public rates |
| - | Headquarters listed differently across sources |
Who should choose Revelo?
A typical fit: hiring a Brazilian ML engineer without a long contract.
No upfront fees, no long-term contract and published salary benchmarks. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Fintech, SaaS, Healthcare, AI labs.
Who should choose N-iX?
A typical fit: extending an enterprise data team.
Three clearly separated engagement models with a large bench. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Manufacturing, Retail, Telecom, Healthcare.
Decision matrix: Revelo vs N-iX
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Both; Revelo rates higher overall |
| You only need a specialist a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| You need a rate before the first call | Neither publishes rates; ask both for a written rate card |
| Your budget is at the lower end | Compare: Revelo (Not published) vs N-iX (Not published) |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
| You want several engineers working as one team | N-iX |
Use case fit: Revelo vs N-iX
| Use case | Revelo fit | N-iX fit | Winner |
|---|---|---|---|
| Hiring a Brazilian ML engineer without a long contract | Strong | Limited | Revelo |
| Budgeting a nearshore AI team from published salary data | Strong | Limited | Revelo |
| Extending an enterprise data team | Limited | Strong | N-iX |
| Switching an augmented team to a managed model | Limited | Strong | N-iX |
Verdict: Revelo vs N-iX
Revelo (4.0/5) is the stronger overall choice for most AI Staff Augmentation projects. No upfront fees, no long-term contract and published salary benchmarks.
N-iX (3.8/5) is worth a look if you need switching an augmented team to a managed model. If your situation matches that, N-iX is a competitive option.
Related comparisons
Revelo vs N-iX FAQ
Is Revelo better than N-iX?
Revelo (4.0/5) scores higher overall, but "better" depends on your use case. Revelo's strongest advantage: no upfront fee or long-term contract. N-iX's strongest advantage: clear engagement models.
How do Revelo and N-iX differ in pricing?
Revelo uses monthly per engineer; no upfront fees or long-term contracts (per company); senior ai/ml all-in cost about $103,000/yr (company benchmark) pricing. N-iX uses monthly per engineer or managed team; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Revelo or N-iX?
Revelo is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each provider before shortlisting.
What are the main differences between Revelo and N-iX?
Revelo's primary differentiator is: no upfront fees, no long-term contract and published salary benchmarks. N-iX's primary differentiator is: three clearly separated engagement models with a large bench. They also differ in team size (400,000+ network (company figure) vs 2,000+), minimum engagement (Not published vs Not published), and primary industries served (Technology, Fintech vs Financial services, Manufacturing).
Verify all details directly with each provider before making a decision.