deepsense.ai vs Nearsure: full comparison for 2026
Quick verdict
deepsense.ai (4.3/5) edges ahead of Nearsure (3.9/5) overall. deepsense.ai is the better choice for research-heavy ML problems, computer vision, edge AI. 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.
deepsense.ai vs Nearsure: head-to-head summary
| Criterion | deepsense.ai | Nearsure |
|---|---|---|
| Founded | 2014 | 2018 |
| HQ | Warsaw, Poland | Montevideo, Uruguay (U.S.-incorporated) |
| Team size | 100–200 | 500–850 (sources vary) |
| Rating | 4.3 / 5 | 3.9 / 5 |
| Primary differentiator | A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench | Augmentation-first business model with a growing AI studio |
| Pricing model | Time and materials for augmented engineers; project contracts; rates on request | Monthly staff augmentation rates; project development; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, OpenAI, AWS |
| Industries served | Manufacturing, Retail & e-commerce, Healthcare & life sciences, Financial services, Software & SaaS | Software & SaaS, Healthcare & life sciences, Financial services |
deepsense.ai vs Nearsure: overview
deepsense.ai
deepsense.ai was founded in 2014, grew out of the AI division of CodiLime, and is headquartered in Warsaw with an office in Palo Alto. Third-party directories put its headcount between roughly 100 and 200 people, and the company says it employs more than 120 AI experts, including Kaggle competition winners and PhD holders. Besides project work in generative AI, MLOps, computer vision and edge AI, it runs a dedicated AI staff augmentation service in which its own engineers extend a client's team.
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: deepsense.ai vs Nearsure
| Capability | deepsense.ai | 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: deepsense.ai vs Nearsure
| Framework / platform | deepsense.ai | Nearsure |
|---|---|---|
| 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 |
| Kubernetes | ✓ | N/A |
Pricing comparison: deepsense.ai vs Nearsure
| Criterion | deepsense.ai | Nearsure |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: deepsense.ai vs Nearsure
| Dimension | deepsense.ai | Nearsure |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail & e-commerce, Healthcare & life sciences | Software & SaaS, Healthcare & life sciences, Financial services |
| Best use cases | Adding a computer-vision specialist to a manufacturing quality team, Bringing research depth into a stalled model-accuracy effort | Adding a GenAI developer to a U.S. SaaS team, Staffing data engineers for a cloud migration |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
deepsense.ai vs Nearsure: pros and cons
| deepsense.ai | |
|---|---|
| + | Every engineer it places comes from an AI-only company |
| + | Strong record in computer vision and edge deployment |
| + | Clutch reviewers describe team-augmentation work with strong engineering skills |
| - | A bench of roughly 120 AI staff limits how many people can start at once |
| - | Polish rates are higher than Ukrainian or Latin American alternatives |
| - | Better suited to hard modeling work than to routine LLM integration |
| 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 deepsense.ai?
A typical fit: adding a computer-vision specialist to a manufacturing quality team.
A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail & e-commerce, Healthcare & life sciences, Financial services, Software & SaaS.
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: deepsense.ai vs Nearsure
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; deepsense.ai rates higher overall |
| You want the supplier to own delivery as well as staffing | deepsense.ai |
| 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: deepsense.ai (Not published) vs Nearsure (Not published) |
| You need overlap with U.S. working hours | Nearsure |
| You need specialist depth in a specific vertical | deepsense.ai |
Use case fit: deepsense.ai vs Nearsure
| Use case | deepsense.ai fit | Nearsure fit | Winner |
|---|---|---|---|
| Adding a computer-vision specialist to a manufacturing quality team | Strong | Strong | Both equally |
| Bringing research depth into a stalled model-accuracy effort | Strong | Limited | deepsense.ai |
| Adding a GenAI developer to a U.S. SaaS team | Strong | Strong | Both equally |
| Staffing data engineers for a cloud migration | Limited | Strong | Nearsure |
Verdict: deepsense.ai vs Nearsure
deepsense.ai (4.3/5) is the stronger overall choice for most AI Staff Augmentation projects. A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench.
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
deepsense.ai vs Nearsure FAQ
Is deepsense.ai better than Nearsure?
deepsense.ai (4.3/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: every engineer it places comes from an AI-only company. Nearsure's strongest advantage: staff augmentation is the main business, so processes are built around it.
How do deepsense.ai and Nearsure differ in pricing?
deepsense.ai uses time and materials for augmented engineers; project 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: deepsense.ai 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 deepsense.ai and Nearsure?
deepsense.ai's primary differentiator is: a pure applied-AI firm whose augmented engineers come from a research-grade data-science bench. Nearsure's primary differentiator is: augmentation-first business model with a growing AI studio. They also differ in team size (100–200 vs 500–850 (sources vary)), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Retail & e-commerce vs Software & SaaS, Healthcare & life sciences).
Verify all details directly with each company before making a decision.