Globant vs 10Clouds: full comparison for 2026
Quick verdict
Globant (4.0/5) edges ahead of 10Clouds (3.8/5) overall. Globant is the better choice for US firms wanting nearshore AI engineering. 10Clouds is the stronger option for smaller banks and lenders adding AI. The right choice depends on how far your pilot has got, your budget, and who will run the system after launch.
Globant vs 10Clouds: head-to-head summary
| Criterion | Globant | 10Clouds |
|---|---|---|
| Founded | 2003 | 2009 |
| HQ | Luxembourg (operations: Buenos Aires) | Warsaw, Poland |
| Team size | 28,500+ | ~200 |
| Rating | 4.0 / 5 | 3.8 / 5 |
| Primary differentiator | Nearshore Latin American engineering teams in US time zones | A dedicated financial-institutions AI unit with its own AIConsole platform |
| Pricing model | Time & materials and dedicated teams; rates not published | Project and team pricing; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Google Cloud, AWS, Azure | AWS, Azure, OpenAI |
| Industries served | Media, Retail, Financial services, Travel, Healthcare | Banking, Fintech, Insurance, Healthcare |
Globant vs 10Clouds: overview
Globant
Globant was founded in 2003 in Buenos Aires, is legally domiciled in Luxembourg, and employs more than 28,500 people. It is listed on the New York Stock Exchange. Its AI work runs through studios that combine design and engineering, with nearshore delivery that keeps time zones close for US clients. Production AI usually comes inside a wider digital product program.
10Clouds
10Clouds was founded in Warsaw in 2009 and has around 200 people across Warsaw, Wrocław, and Poznań. It set up a separate company, 10Clouds Financial Institutions, to build AI operations for banks and lenders, and it has its own AI platform called AIConsole. Most of its history is custom software and blockchain work, with AI the newest focus.
Services and capabilities: Globant vs 10Clouds
| Capability | Globant | 10Clouds |
|---|---|---|
| LLM gateway & model routing | ✗ | ✗ |
| Regression tests on prompt and model changes | ✗ | ✗ |
| Canary or staged rollout | ✗ | ✗ |
| Hallucination and drift monitoring | ✗ | ✗ |
| MLOps & model serving | ✗ | ✗ |
| Fixed-scope pilot | ✗ | ✗ |
| Managed run after launch | ✗ | ✗ |
Tech stack comparison: Globant vs 10Clouds
| Framework / platform | Globant | 10Clouds |
|---|---|---|
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Kubernetes | N/A | N/A |
| MLflow | N/A | N/A |
| Databricks | ✓ | N/A |
| Amazon Bedrock | N/A | N/A |
| Vertex AI | N/A | N/A |
| LangChain | N/A | N/A |
| Snowflake | N/A | N/A |
Pricing comparison: Globant vs 10Clouds
| Criterion | Globant | 10Clouds |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Time & materials, Dedicated team | Fixed-scope project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Globant vs 10Clouds
| Dimension | Globant | 10Clouds |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Media, Retail, Financial services | Banking, Fintech, Insurance |
| Best use cases | AI features inside consumer digital products., Nearshore AI engineering teams for US companies. | AI-assisted operations at a smaller bank or lender., Customer service assistants in fintech. |
| Typical project type | Time & materials | Fixed-scope project |
Globant vs 10Clouds: pros and cons
| Globant | |
|---|---|
| + | Nearshore teams share working hours with US clients |
| + | Large design and engineering capacity |
| + | Public company with regular disclosures |
| - | AI is one part of a broad digital business |
| - | Large-firm process for small pilots |
| - | Rates not published |
| 10Clouds | |
|---|---|
| + | Dedicated unit for banks and lenders |
| + | Own AI platform to start from |
| + | Nearshore rates |
| - | AI is a recent focus for the firm |
| - | Small team for large programs |
| - | Little public detail on monitoring or rollout practice |
Who should choose Globant?
A typical fit: AI features inside consumer digital products.
Nearshore Latin American engineering teams in US time zones. Minimum engagement is not publicly disclosed. Works best with clients in Media, Retail, Financial services, Travel, Healthcare.
Who should choose 10Clouds?
A typical fit: AI-assisted operations at a smaller bank or lender.
A dedicated financial-institutions AI unit with its own AIConsole platform. Minimum engagement is not publicly disclosed. Works best with clients in Banking, Fintech, Insurance, Healthcare.
Decision matrix: Globant vs 10Clouds
| Your situation | Recommended choice |
|---|---|
| Your pilot works but nobody trusts it in production yet | Ask each for its release and rollback process |
| Model API spend is growing faster than usage | Neither lists a gateway; ask how cost per feature is tracked |
| You need someone to watch quality after launch | Neither; plan for your own team to monitor it |
| You run classic ML models that need serving and retraining | Neither lists MLOps; check each profile |
| You want a priced pilot before a full rollout | Neither advertises one; ask for a scoped quote |
| Your budget is at the lower end | Compare: Globant (Not disclosed) vs 10Clouds (Not disclosed) |
| You need a large team for many products at once | Globant |
Use case fit: Globant vs 10Clouds
| Use case | Globant fit | 10Clouds fit | Winner |
|---|---|---|---|
| AI features inside consumer digital products. | Strong | Limited | Globant |
| Nearshore AI engineering teams for US companies. | Strong | Limited | Globant |
| AI-assisted operations at a smaller bank or lender. | Limited | Strong | 10Clouds |
| Customer service assistants in fintech. | Limited | Strong | 10Clouds |
Verdict: Globant vs 10Clouds
Globant (4.0/5) is the stronger overall choice for most AI Implementation projects. Nearshore Latin American engineering teams in US time zones.
10Clouds (3.8/5) is worth a look if you need customer service assistants in fintech. If your situation matches that, 10Clouds is a competitive option.
Related comparisons
Globant vs 10Clouds FAQ
Is Globant better than 10Clouds?
Globant (4.0/5) scores higher overall, but "better" depends on your use case. Globant's strongest advantage: nearshore teams share working hours with US clients. 10Clouds's strongest advantage: dedicated unit for banks and lenders.
How do Globant and 10Clouds differ in pricing?
Globant's pricing: time & materials and dedicated teams; rates not published. 10Clouds's pricing: project and team pricing; rates on request. Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: Globant or 10Clouds?
Globant 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 Globant and 10Clouds?
Globant's primary differentiator is: nearshore Latin American engineering teams in US time zones. 10Clouds's primary differentiator is: a dedicated financial-institutions AI unit with its own AIConsole platform. They also differ in team size (28,500+ vs ~200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Media, Retail vs Banking, Fintech).
Verify all details directly with each provider before making a decision.