Globant vs Nearsure: full comparison for 2026
Quick verdict
Globant (4.1/5) edges ahead of Nearsure (3.9/5) overall. Globant is the better choice for enterprises wanting AI capacity on a subscription model. Nearsure is the stronger option for U.S. teams adding Latin American GenAI developers. The right choice depends on your project size, budget, and required tech stack.
Globant vs Nearsure: head-to-head summary
| Criterion | Globant | Nearsure |
|---|---|---|
| Founded | 2003 | 2018 |
| HQ | Luxembourg | Montevideo, Uruguay (U.S.-incorporated) |
| Team size | 28,000+ | 500–850 (sources vary) |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Subscription-based AI Pods as an alternative to per-engineer billing | Augmentation-first business model with a growing AI studio |
| Pricing model | AI Pods monthly subscription with token-based capacity; staff augmentation and SOW contracts; rates on request | Monthly staff augmentation rates; project development; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, OpenAI, Azure ML | Python, OpenAI, AWS |
| Industries served | Media, Financial services, Travel, Retail & e-commerce, Healthcare & life sciences | Software & SaaS, Healthcare & life sciences, Financial services |
Globant vs Nearsure: overview
Globant
Globant was founded in Buenos Aires in 2003 and is now headquartered in Luxembourg. The NYSE-listed company reported 28,773 employees at the end of 2025. In 2025 it launched AI Pods, a monthly subscription for AI-assisted engineering capacity metered by tokens. Third-party reviews say classic staff augmentation runs mainly through Belatrix, a firm Globant acquired, while large accounts usually buy managed pods or statements of work.
Nearsure
Nearsure started operations in 2018 under co-founder and CEO Giuliana Corbo and is described by Bloomberg as a Uruguayan IT services company, though it is incorporated in the United States. Bloomberg reported a 2024 plan to grow to about 850 staff. Remote staff augmentation for U.S. clients is its core business, and the service list has widened to generative AI, cloud migration and Salesforce work through a Data & AI studio.
Services and capabilities: Globant vs Nearsure
| Capability | Globant | Nearsure |
|---|---|---|
| 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: Globant vs Nearsure
| Framework / platform | Globant | Nearsure |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Globant vs Nearsure
| Criterion | Globant | Nearsure |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated team, Managed delivery, Full-time dedicated engineers | Full-time dedicated engineers, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Globant vs Nearsure
| Dimension | Globant | Nearsure |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Media, Financial services, Travel | Software & SaaS, Healthcare & life sciences, Financial services |
| Best use cases | Buying a monthly AI engineering pod for a marketing-tech roadmap, Staffing agent development across several brands | Adding a GenAI developer to a U.S. SaaS team, Staffing data engineers for a cloud migration |
| Typical project type | Dedicated team | Full-time dedicated engineers |
Globant vs Nearsure: pros and cons
| Globant | |
|---|---|
| + | AI Pods give finance teams a predictable monthly cost |
| + | Large Latin American delivery footprint on U.S.-friendly hours |
| + | Public-company governance suits procurement-heavy buyers |
| - | Individual staff augmentation is a side channel run largely through the acquired Belatrix business |
| - | Headcount fell about 8% during 2025, according to Bloomberg Línea |
| - | Pod and token-based pricing is hard to compare with per-engineer quotes |
| Nearsure | |
|---|---|
| + | Staff augmentation is the main business, so processes are built around it |
| + | Latin American engineers on U.S. hours |
| + | Has been profitable since early in its history, per AméricaEconomía |
| - | AI is a newer studio inside a general staffing company |
| - | Headcount reports vary between 525 and 850 |
| - | HQ location differs between sources |
Who should choose Globant?
A typical fit: buying a monthly AI engineering pod for a marketing-tech roadmap.
Subscription-based AI Pods as an alternative to per-engineer billing. Minimum engagement is not publicly disclosed. Works best with clients in Media, Financial services, Travel, Retail & e-commerce, Healthcare & life sciences.
Who should choose Nearsure?
A typical fit: adding a GenAI developer to a U.S. SaaS team.
Augmentation-first business model with a growing AI studio. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Financial services.
Decision matrix: Globant vs Nearsure
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; Globant rates higher overall |
| You want the supplier to own delivery as well as staffing | Globant |
| 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: Globant (Not published) vs Nearsure (Not published) |
| You need overlap with U.S. working hours | Both; Globant rates higher overall |
| You need specialist depth in a specific vertical | Globant |
Use case fit: Globant vs Nearsure
| Use case | Globant fit | Nearsure fit | Winner |
|---|---|---|---|
| Buying a monthly AI engineering pod for a marketing-tech roadmap | Strong | Limited | Globant |
| Staffing agent development across several brands | Strong | Strong | Both equally |
| Adding a GenAI developer to a U.S. SaaS team | Limited | Strong | Nearsure |
| Staffing data engineers for a cloud migration | Strong | Strong | Both equally |
Verdict: Globant vs Nearsure
Globant (4.1/5) is the stronger overall choice for most AI Staff Augmentation projects. Subscription-based AI Pods as an alternative to per-engineer billing.
Nearsure (3.9/5) is worth a look if you need staffing data engineers for a cloud migration. If your situation matches that, Nearsure is a competitive option.
Related comparisons
Globant vs Nearsure FAQ
Is Globant better than Nearsure?
Globant (4.1/5) scores higher overall, but "better" depends on your use case. Globant's strongest advantage: AI Pods give finance teams a predictable monthly cost. Nearsure's strongest advantage: staff augmentation is the main business, so processes are built around it.
How do Globant and Nearsure differ in pricing?
Globant uses ai pods monthly subscription with token-based capacity; staff augmentation and sow contracts; rates on request pricing. Nearsure uses monthly staff augmentation rates; project development; 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: Globant or Nearsure?
Nearsure 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 Globant and Nearsure?
Globant's primary differentiator is: subscription-based AI Pods as an alternative to per-engineer billing. Nearsure's primary differentiator is: augmentation-first business model with a growing AI studio. They also differ in team size (28,000+ vs 500–850 (sources vary)), minimum engagement (Not published vs Not published), and primary industries served (Media, Financial services vs Software & SaaS, Healthcare & life sciences).
Verify all details directly with each company before making a decision.