nCube vs Howdy.com: full comparison for 2026
Quick verdict
nCube (3.9/5) edges ahead of Howdy.com (3.9/5) overall. nCube is the better choice for companies building a long-term offshore AI team. Howdy.com is the stronger option for U.S. startups hiring full-time Latin American AI engineers. The right choice depends on your project size, budget, and required tech stack.
nCube vs Howdy.com: head-to-head summary
| Criterion | nCube | Howdy.com |
|---|---|---|
| Founded | 2008 | 2018 |
| HQ | London, UK | Austin, Texas, USA |
| Team size | 50–249 staff; large external talent pool (per company) | Not disclosed |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | Builds and runs a client-branded R&D team, including HR and office setup | Full-time, single-client placements with employment handled by Howdy |
| Pricing model | Monthly per-engineer team pricing; free vetting until candidates are chosen; rates on request | Monthly all-in fee per engineer quoted per engagement; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, OpenAI, LangChain |
| Industries served | Software & SaaS, Media, Financial services, Manufacturing | Software & SaaS, Financial services, Healthcare & life sciences |
nCube vs Howdy.com: overview
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.
Howdy.com
Howdy.com was founded in Austin, Texas, in 2018 to connect Latin American engineers with U.S. companies, and it acquired the Brazilian talent marketplace GeekHunter to expand its pool. Engineers work full time for one client while Howdy handles employment, benefits and equipment. The company now markets itself around AI-capable engineers, and pricing is quoted per engagement rather than published.
Services and capabilities: nCube vs Howdy.com
| Capability | nCube | Howdy.com |
|---|---|---|
| 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: nCube vs Howdy.com
| Framework / platform | nCube | Howdy.com |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Databricks | N/A | N/A |
| MLflow | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: nCube vs Howdy.com
| Criterion | nCube | Howdy.com |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated team, Full-time dedicated engineers | Full-time dedicated engineers |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: nCube vs Howdy.com
| Dimension | nCube | Howdy.com |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Software & SaaS, Media, Financial services | Software & SaaS, Financial services, Healthcare & life sciences |
| Best use cases | Setting up a five-person ML team in Eastern Europe, Building a computer-vision team for a media analytics product | Hiring one full-time LLM application developer for a startup, Building a small Latin American team on U.S. hours |
| Typical project type | Dedicated team | Full-time dedicated engineers |
nCube vs Howdy.com: pros and cons
| 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 |
| Howdy.com | |
|---|---|
| + | Engineers work for one client full time |
| + | Howdy covers benefits, equipment and local employment |
| + | GeekHunter acquisition widened access to Brazilian talent |
| - | Company headcount is not disclosed |
| - | No published rates despite transparent-pricing marketing |
| - | AI focus is a recent repositioning |
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.
Who should choose Howdy.com?
A typical fit: hiring one full-time LLM application developer for a startup.
Full-time, single-client placements with employment handled by Howdy. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Financial services, Healthcare & life sciences.
Decision matrix: nCube vs Howdy.com
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; nCube rates higher overall |
| You want the supplier to own delivery as well as staffing | Neither offers managed delivery; you will lead the work |
| 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: nCube (Not published) vs Howdy.com (Not published) |
| You need overlap with U.S. working hours | Howdy.com |
| You need specialist depth in a specific vertical | nCube |
Use case fit: nCube vs Howdy.com
| Use case | nCube fit | Howdy.com fit | Winner |
|---|---|---|---|
| Setting up a five-person ML team in Eastern Europe | Strong | Limited | nCube |
| Building a computer-vision team for a media analytics product | Strong | Strong | Both equally |
| Hiring one full-time LLM application developer for a startup | Limited | Strong | Howdy.com |
| Building a small Latin American team on U.S. hours | Strong | Strong | Both equally |
Verdict: nCube vs Howdy.com
nCube (3.9/5) is the stronger overall choice for most AI Staff Augmentation projects. Builds and runs a client-branded R&D team, including HR and office setup.
Howdy.com (3.9/5) is worth a look if you need building a small Latin American team on U.S. hours. If your situation matches that, Howdy.com is a competitive option.
Related comparisons
nCube vs Howdy.com FAQ
Is nCube better than Howdy.com?
nCube (3.9/5) scores higher overall, but "better" depends on your use case. nCube's strongest advantage: handles the HR, payroll and legal side of a remote team. Howdy.com's strongest advantage: engineers work for one client full time.
How do nCube and Howdy.com differ in pricing?
nCube uses monthly per-engineer team pricing; free vetting until candidates are chosen; rates on request pricing. Howdy.com uses monthly all-in fee per engineer quoted per engagement; 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: nCube or Howdy.com?
nCube 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 nCube and Howdy.com?
nCube's primary differentiator is: builds and runs a client-branded R&D team, including HR and office setup. Howdy.com's primary differentiator is: Full-time, single-client placements with employment handled by Howdy. They also differ in team size (50–249 staff; large external talent pool (per company) vs Not disclosed), minimum engagement (Not published vs Not published), and primary industries served (Software & SaaS, Media vs Software & SaaS, Financial services).
Verify all details directly with each company before making a decision.