Azumo vs nCube: full comparison for 2026
Quick verdict
Azumo (4.1/5) edges ahead of nCube (3.9/5) overall. Azumo is the better choice for nearshore LLM and NLP builds for U.S. mid-market. nCube is the stronger option for companies building a long-term offshore AI team. The right choice depends on your project size, budget, and required tech stack.
Azumo vs nCube: head-to-head summary
| Criterion | Azumo | nCube |
|---|---|---|
| Founded | 2016 | 2008 |
| HQ | San Francisco, California, USA | London, UK |
| Team size | 100–500 (sources vary) | 50–249 staff; large external talent pool (per company) |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | A nearshore team that also builds its own NLP products | Builds and runs a client-branded R&D team, including HR and office setup |
| Pricing model | Monthly rates for augmented engineers; dedicated teams; project pricing; rates on request | Monthly per-engineer team pricing; free vetting until candidates are chosen; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, LangChain, OpenAI | Python, PyTorch, TensorFlow |
| Industries served | Healthcare & life sciences, Media, Software & SaaS, Financial services | Software & SaaS, Media, Financial services, Manufacturing |
Azumo vs nCube: overview
Azumo
Azumo is headquartered in San Francisco and has built AI-driven applications since 2016, with most of its engineers in Latin America. Directory headcounts range from under 100 to several hundred people. It offers staff augmentation, dedicated teams and full product outsourcing, and it also maintains its own AI products, including an NLU toolkit. Named clients include Meta and UnitedHealth (per company website; independently unverifiable).
nCube
nCube was founded in 2008 and is registered in London, with its core R&D office in Kyiv and development offices in Warsaw and São Paulo. It builds dedicated teams and nearshore R&D centers, handling hiring, payroll, legal and HR for the client. The company says it can show first AI candidate profiles within 48 hours and build a team in two to six weeks, drawing on a pool of more than 50,000 AI, ML and data specialists (per company website; independently unverifiable). Named AI clients include Veritone and Fetch.ai.
Services and capabilities: Azumo vs nCube
| Capability | Azumo | nCube |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✗ |
| MLOps & deployment | ✗ | ✓ |
| Computer vision | ✗ | ✓ |
| Data engineering | ✗ | ✗ |
| AI agent development | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✓ | ✗ |
Tech stack comparison: Azumo vs nCube
| Framework / platform | Azumo | nCube |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | ✓ |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | N/A | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: Azumo vs nCube
| Criterion | Azumo | nCube |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Dedicated team, Full-time dedicated engineers |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Azumo vs nCube
| Dimension | Azumo | nCube |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare & life sciences, Media, Software & SaaS | Software & SaaS, Media, Financial services |
| Best use cases | Adding a conversational-AI engineer to a healthcare app team, Building a document-search assistant on internal knowledge | Setting up a five-person ML team in Eastern Europe, Building a computer-vision team for a media analytics product |
| Typical project type | Full-time dedicated engineers | Dedicated team |
Azumo vs nCube: pros and cons
| Azumo | |
|---|---|
| + | Its own AI products show applied NLP experience |
| + | Latin American engineers share U.S. working hours |
| + | Flexible mix of augmentation and project delivery |
| - | Headcount reports vary widely, so ask how many AI engineers are actually on staff |
| - | Smaller bench than the large nearshore firms on this list |
| - | Founding year differs across sources (2013 or 2016) |
| nCube | |
|---|---|
| + | Handles the HR, payroll and legal side of a remote team |
| + | AI client list includes Veritone and Fetch.ai |
| + | Vetting is free until you pick candidates |
| - | Core team is small relative to the talent pool it advertises |
| - | Two to six weeks is slower than marketplace matching |
| - | Contract notice terms are not published |
Who should choose Azumo?
A typical fit: adding a conversational-AI engineer to a healthcare app team.
A nearshore team that also builds its own NLP products. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare & life sciences, Media, Software & SaaS, Financial services.
Who should choose nCube?
A typical fit: setting up a five-person ML team in Eastern Europe.
Builds and runs a client-branded R&D team, including HR and office setup. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Media, Financial services, Manufacturing.
Decision matrix: Azumo vs nCube
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; Azumo rates higher overall |
| You want the supplier to own delivery as well as staffing | Azumo |
| You need one expert part-time | Neither lists part-time experts; ask about reduced hours |
| You want to test an engineer before signing for months | Neither publishes a trial; ask for a short first term |
| Your budget is at the lower end | Compare: Azumo (Not published) vs nCube (Not published) |
| You need overlap with U.S. working hours | Azumo |
| You need specialist depth in a specific vertical | Azumo |
Use case fit: Azumo vs nCube
| Use case | Azumo fit | nCube fit | Winner |
|---|---|---|---|
| Adding a conversational-AI engineer to a healthcare app team | Strong | Limited | Azumo |
| Building a document-search assistant on internal knowledge | Strong | Strong | Both equally |
| Setting up a five-person ML team in Eastern Europe | Limited | Strong | nCube |
| Building a computer-vision team for a media analytics product | Strong | Strong | Both equally |
Verdict: Azumo vs nCube
Azumo (4.1/5) is the stronger overall choice for most AI Staff Augmentation projects. A nearshore team that also builds its own NLP products.
nCube (3.9/5) is worth a look if you need building a computer-vision team for a media analytics product. If your situation matches that, nCube is a competitive option.
Related comparisons
Azumo vs nCube FAQ
Is Azumo better than nCube?
Azumo (4.1/5) scores higher overall, but "better" depends on your use case. Azumo's strongest advantage: its own AI products show applied NLP experience. nCube's strongest advantage: handles the HR, payroll and legal side of a remote team.
How do Azumo and nCube differ in pricing?
Azumo uses monthly rates for augmented engineers; dedicated teams; project pricing; rates on request pricing. nCube uses monthly per-engineer team pricing; free vetting until candidates are chosen; 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: Azumo or nCube?
Azumo 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 Azumo and nCube?
Azumo's primary differentiator is: a nearshore team that also builds its own NLP products. nCube's primary differentiator is: builds and runs a client-branded R&D team, including HR and office setup. They also differ in team size (100–500 (sources vary) vs 50–249 staff; large external talent pool (per company)), minimum engagement (Not published vs Not published), and primary industries served (Healthcare & life sciences, Media vs Software & SaaS, Media).
Verify all details directly with each company before making a decision.