Nearsure vs Xenoss: full comparison for 2026
Quick verdict
Nearsure (3.9/5) edges ahead of Xenoss (3.8/5) overall. Nearsure is the better choice for U.S. teams adding Latin American GenAI developers. Xenoss is the stronger option for AdTech and MarTech firms needing real-time data plus AI. The right choice depends on your project size, budget, and required tech stack.
Nearsure vs Xenoss: head-to-head summary
| Criterion | Nearsure | Xenoss |
|---|---|---|
| Founded | 2018 | 2013 |
| HQ | Montevideo, Uruguay (U.S.-incorporated) | New York, New York, USA |
| Team size | 500–850 (sources vary) | 100–200 |
| Rating | 3.9 / 5 | 3.8 / 5 |
| Primary differentiator | Augmentation-first business model with a growing AI studio | Real-time, high-load data engineering from AdTech roots |
| Pricing model | Monthly staff augmentation rates; project development; rates on request | Team extension and project pricing; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, OpenAI, AWS | Python, Kafka, Spark |
| Industries served | Software & SaaS, Healthcare & life sciences, Financial services | Media, Retail & e-commerce, Software & SaaS |
Nearsure vs Xenoss: overview
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.
Xenoss
Xenoss was founded in 2013 by AdTech veterans and lists its headquarters in New York, with CEO Dmitry Sverdlik. Directories put headcount between 100 and 200. It specializes in AI and data engineering, including AI agents, real-time data systems and LLM knowledge bases, and favors small senior teams. Team extension appears in its history, but it does not run a dedicated staff augmentation offer.
Services and capabilities: Nearsure vs Xenoss
| Capability | Nearsure | Xenoss |
|---|---|---|
| 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: Nearsure vs Xenoss
| Framework / platform | Nearsure | Xenoss |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | N/A | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Nearsure vs Xenoss
| Criterion | Nearsure | Xenoss |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team | Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Nearsure vs Xenoss
| Dimension | Nearsure | Xenoss |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Software & SaaS, Healthcare & life sciences, Financial services | Media, Retail & e-commerce, Software & SaaS |
| Best use cases | Adding a GenAI developer to a U.S. SaaS team, Staffing data engineers for a cloud migration | Adding real-time feature engineering for a bidding model, Building an LLM knowledge base on marketing data |
| Typical project type | Full-time dedicated engineers | Dedicated team |
Nearsure vs Xenoss: pros and cons
| 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 |
| Xenoss | |
|---|---|
| + | High-load, real-time data experience |
| + | Small senior teams with low management overhead |
| + | Builds agents and knowledge bases on its own data work |
| - | No dedicated staff augmentation page |
| - | Industry focus is narrow outside AdTech and MarTech |
| - | Headcount data varies |
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.
Who should choose Xenoss?
A typical fit: adding real-time feature engineering for a bidding model.
Real-time, high-load data engineering from AdTech roots. Minimum engagement is not publicly disclosed. Works best with clients in Media, Retail & e-commerce, Software & SaaS.
Decision matrix: Nearsure vs Xenoss
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; Nearsure rates higher overall |
| You want the supplier to own delivery as well as staffing | Xenoss |
| 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: Nearsure (Not published) vs Xenoss (Not published) |
| You need overlap with U.S. working hours | Nearsure |
| You need specialist depth in a specific vertical | Nearsure |
Use case fit: Nearsure vs Xenoss
| Use case | Nearsure fit | Xenoss fit | Winner |
|---|---|---|---|
| Adding a GenAI developer to a U.S. SaaS team | Strong | Strong | Both equally |
| Staffing data engineers for a cloud migration | Strong | Limited | Nearsure |
| Adding real-time feature engineering for a bidding model | Strong | Strong | Both equally |
| Building an LLM knowledge base on marketing data | Limited | Strong | Xenoss |
Verdict: Nearsure vs Xenoss
Nearsure (3.9/5) is the stronger overall choice for most AI Staff Augmentation projects. Augmentation-first business model with a growing AI studio.
Xenoss (3.8/5) is worth a look if you need building an LLM knowledge base on marketing data. If your situation matches that, Xenoss is a competitive option.
Related comparisons
Nearsure vs Xenoss FAQ
Is Nearsure better than Xenoss?
Nearsure (3.9/5) scores higher overall, but "better" depends on your use case. Nearsure's strongest advantage: staff augmentation is the main business, so processes are built around it. Xenoss's strongest advantage: High-load, real-time data experience.
How do Nearsure and Xenoss differ in pricing?
Nearsure uses monthly staff augmentation rates; project development; rates on request pricing. Xenoss uses team extension and project pricing; 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: Nearsure or Xenoss?
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 Nearsure and Xenoss?
Nearsure's primary differentiator is: augmentation-first business model with a growing AI studio. Xenoss's primary differentiator is: Real-time, high-load data engineering from AdTech roots. They also differ in team size (500–850 (sources vary) vs 100–200), minimum engagement (Not published vs Not published), and primary industries served (Software & SaaS, Healthcare & life sciences vs Media, Retail & e-commerce).
Verify all details directly with each company before making a decision.