Revelo vs Simform: full comparison for 2026
Quick verdict
Revelo (3.8/5) edges ahead of Simform (3.8/5) overall. Revelo is the better choice for hiring Latin American developers through a marketplace. Simform is the stronger option for cloud-first companies adding AI and data engineers. The right choice depends on your project size, budget, and required tech stack.
Revelo vs Simform: head-to-head summary
| Criterion | Revelo | Simform |
|---|---|---|
| Founded | 2014 | 2010 |
| HQ | São Paulo, Brazil | Orlando, Florida, USA |
| Team size | 400,000+ developer network (per company) | 1,000+ |
| Rating | 3.8 / 5 | 3.8 / 5 |
| Primary differentiator | A very large Latin American pool with payroll and compliance included | Cloud and data engineering paired with AI/ML from an India-based bench |
| Pricing model | Marketplace placement with monthly billing; rates on request | Time and materials; dedicated teams; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, OpenAI, Hugging Face | Python, Azure ML, AWS SageMaker |
| Industries served | Software & SaaS, AI research labs, Financial services | Software & SaaS, Healthcare & life sciences, Retail & e-commerce, Logistics |
Revelo vs Simform: overview
Revelo
Revelo was founded in late 2014 in Brazil (some sources say 2015) and began as a domestic hiring platform called Contratado. It now runs a network of more than 400,000 Latin American developers and handles hiring and payment for U.S. customers. TechCrunch reported that work on foundation models made up 22% of Revelo's revenue in 2024. Revelo is a marketplace, so engineers are matched through its platform rather than employed in a delivery center.
Simform
Simform was founded in 2010 and lists its primary location in Orlando, Florida, with a large delivery center in Ahmedabad, India. Clutch places it in the 1,000 to 9,999 employee range. Its positioning centers on cloud, data, AI/ML and experience engineering, and Clutch reviewers describe staff augmentation engagements covering DevOps, frontend and backend roles.
Services and capabilities: Revelo vs Simform
| Capability | Revelo | Simform |
|---|---|---|
| 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: Revelo vs Simform
| Framework / platform | Revelo | Simform |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: Revelo vs Simform
| Criterion | Revelo | Simform |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Revelo vs Simform
| Dimension | Revelo | Simform |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Software & SaaS, AI research labs, Financial services | Software & SaaS, Healthcare & life sciences, Retail & e-commerce |
| Best use cases | Hiring LLM data specialists for a model-training effort, Adding a Brazilian developer to a U.S. SaaS team | Adding an Azure ML engineer to a cloud team, Staffing data engineers for a SaaS analytics feature |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
Revelo vs Simform: pros and cons
| Revelo | |
|---|---|
| + | Very large pool across Latin America |
| + | Handles hiring, payroll and compliance |
| + | Foundation-model work gives some engineers LLM training experience |
| - | Marketplace matching means quality varies by candidate |
| - | Founding year is reported as both 2014 and 2015 |
| - | Less hands-on management than employer-based firms |
| Simform | |
|---|---|
| + | Cloud and data skills support production AI |
| + | India-based delivery keeps costs moderate |
| + | Large enough to staff several roles |
| - | Limited working-hour overlap with U.S. teams |
| - | Reviewed augmentation work is mostly general engineering |
| - | AI depth is harder to verify than at specialist firms |
Who should choose Revelo?
A typical fit: hiring LLM data specialists for a model-training effort.
A very large Latin American pool with payroll and compliance included. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, AI research labs, Financial services.
Who should choose Simform?
A typical fit: adding an Azure ML engineer to a cloud team.
Cloud and data engineering paired with AI/ML from an India-based bench. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Retail & e-commerce, Logistics.
Decision matrix: Revelo vs Simform
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Simform |
| You want the supplier to own delivery as well as staffing | Simform |
| 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: Revelo (Not published) vs Simform (Not published) |
| You need overlap with U.S. working hours | Revelo |
| You need specialist depth in a specific vertical | Simform |
Use case fit: Revelo vs Simform
| Use case | Revelo fit | Simform fit | Winner |
|---|---|---|---|
| Hiring LLM data specialists for a model-training effort | Strong | Limited | Revelo |
| Adding a Brazilian developer to a U.S. SaaS team | Strong | Strong | Both equally |
| Adding an Azure ML engineer to a cloud team | Strong | Strong | Both equally |
| Staffing data engineers for a SaaS analytics feature | Limited | Strong | Simform |
Verdict: Revelo vs Simform
Revelo (3.8/5) is the stronger overall choice for most AI Staff Augmentation projects. A very large Latin American pool with payroll and compliance included.
Simform (3.8/5) is worth a look if you need staffing data engineers for a SaaS analytics feature. If your situation matches that, Simform is a competitive option.
Related comparisons
Revelo vs Simform FAQ
Is Revelo better than Simform?
Revelo (3.8/5) scores higher overall, but "better" depends on your use case. Revelo's strongest advantage: very large pool across Latin America. Simform's strongest advantage: cloud and data skills support production AI.
How do Revelo and Simform differ in pricing?
Revelo uses marketplace placement with monthly billing; rates on request pricing. Simform uses time and materials; dedicated teams; 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: Revelo or Simform?
Revelo 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 Revelo and Simform?
Revelo's primary differentiator is: a very large Latin American pool with payroll and compliance included. Simform's primary differentiator is: cloud and data engineering paired with AI/ML from an India-based bench. They also differ in team size (400,000+ developer network (per company) vs 1,000+), minimum engagement (Not published vs Not published), and primary industries served (Software & SaaS, AI research labs vs Software & SaaS, Healthcare & life sciences).
Verify all details directly with each company before making a decision.