Revelo vs Mercor: full comparison for 2026
Quick verdict
Revelo (4.0/5) edges ahead of Mercor (3.6/5) overall. Revelo is the better choice for U.S. companies that want a Latin American AI engineer without upfront fees or a long contract. Mercor is the stronger option for AI labs buying short-term expert work in volume. The right choice depends on your project size, budget, and required tech stack.
Revelo vs Mercor: head-to-head summary
| Criterion | Revelo | Mercor |
|---|---|---|
| Founded | 2014 | 2023 |
| HQ | Miami, Florida, USA | San Francisco, California, USA |
| Team size | 400,000+ network (company figure) | 300–400 staff; large contractor network |
| Rating | 4.0 / 5 | 3.6 / 5 |
| Primary differentiator | No upfront fees, no long-term contract and published salary benchmarks | Volume contractor hiring with a percentage platform fee |
| Pricing model | Monthly per engineer; no upfront fees or long-term contracts (per company); senior AI/ML all-in cost about $103,000/yr (company benchmark) | Contractor rate plus platform fee (about 30%, Sacra estimate) |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, PyTorch, OpenAI |
| Industries served | Technology, Fintech, SaaS, Healthcare, AI labs | AI labs, Technology, Finance, Legal, Healthcare |
Revelo vs Mercor: overview
Revelo
Revelo started in 2014 (one listing says 2015) and has a U.S. base in Miami and operations in São Paulo. It places engineers from a Latin American network it puts at over 400,000, and its platform pages promise no upfront fees and no long-term contracts. Revelo also publishes salary benchmarks. Its figure for a senior AI or ML engineer is about $103,000 a year all-in, roughly 55% below a comparable U.S. hire. LLM training work made up 22% of its 2024 revenue, according to TechCrunch.
Mercor
Mercor was founded in San Francisco in 2023, employs roughly 300 to 400 people and screens applicants with AI interviews. It raised money at a $10 billion valuation in October 2025, mainly on the strength of supplying experts to AI labs. Its fee is the clearest thing to understand about buying from it: Sacra estimates it at about 30% on top of contractor pay. That model suits large, short-term expert work. For a year-long engineering seat, the fee adds up.
Services and capabilities: Revelo vs Mercor
| Capability | Revelo | Mercor |
|---|---|---|
| Full-time dedicated engineers | ✓ | ✗ |
| Part-time / fractional experts | ✗ | ✗ |
| Dedicated team | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Published rates | ✗ | ✗ |
| Direct hire option | ✗ | ✗ |
| Subscription or output-based pricing | ✗ | ✗ |
| Nearshore time-zone overlap | ✓ | ✗ |
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✗ | ✗ |
Tech stack comparison: Revelo vs Mercor
| Framework / platform | Revelo | Mercor |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Revelo vs Mercor
| Criterion | Revelo | Mercor |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated, Freelance contract | Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Revelo vs Mercor
| Dimension | Revelo | Mercor |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Technology, Fintech, SaaS | AI labs, Technology, Finance |
| Best use cases | Hiring a Brazilian ML engineer without a long contract, Budgeting a nearshore AI team from published salary data | Hiring domain experts to evaluate a model, Adding a contract ML engineer for a research sprint |
| Typical project type | Full-time dedicated | Freelance contract |
Revelo vs Mercor: pros and cons
| Revelo | |
|---|---|
| + | No upfront fee or long-term contract |
| + | Published salary benchmarks help with budgeting |
| + | Large Latin American network on U.S. hours |
| - | Part of revenue comes from AI-lab training work |
| - | Salary figures come from Revelo itself |
| - | Founding year and headquarters differ by source |
| Mercor | |
|---|---|
| + | Fast access to specialists |
| + | Simple percentage pricing |
| + | Well funded |
| - | About 30% fee on a long engagement |
| - | AI interviews, not engineers, do the first screen |
| - | Short track record with product teams |
Who should choose Revelo?
A typical fit: hiring a Brazilian ML engineer without a long contract.
No upfront fees, no long-term contract and published salary benchmarks. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Fintech, SaaS, Healthcare, AI labs.
Who should choose Mercor?
A typical fit: hiring domain experts to evaluate a model.
Volume contractor hiring with a percentage platform fee. Minimum engagement is not publicly disclosed. Works best with clients in AI labs, Technology, Finance, Legal, Healthcare.
Decision matrix: Revelo vs Mercor
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Revelo |
| You only need a specialist a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| You need a rate before the first call | Neither publishes rates; ask both for a written rate card |
| Your budget is at the lower end | Compare: Revelo (Not published) vs Mercor (Not published) |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
| You want several engineers working as one team | Neither lists dedicated teams; check team size before signing |
Use case fit: Revelo vs Mercor
| Use case | Revelo fit | Mercor fit | Winner |
|---|---|---|---|
| Hiring a Brazilian ML engineer without a long contract | Strong | Strong | Both equally |
| Budgeting a nearshore AI team from published salary data | Strong | Limited | Revelo |
| Hiring domain experts to evaluate a model | Strong | Strong | Both equally |
| Adding a contract ML engineer for a research sprint | Strong | Strong | Both equally |
Verdict: Revelo vs Mercor
Revelo (4.0/5) is the stronger overall choice for most AI Staff Augmentation projects. No upfront fees, no long-term contract and published salary benchmarks.
Mercor (3.6/5) is worth a look if you need adding a contract ML engineer for a research sprint. If your situation matches that, Mercor is a competitive option.
Related comparisons
Revelo vs Mercor FAQ
Is Revelo better than Mercor?
Revelo (4.0/5) scores higher overall, but "better" depends on your use case. Revelo's strongest advantage: no upfront fee or long-term contract. Mercor's strongest advantage: fast access to specialists.
How do Revelo and Mercor differ in pricing?
Revelo uses monthly per engineer; no upfront fees or long-term contracts (per company); senior ai/ml all-in cost about $103,000/yr (company benchmark) pricing. Mercor uses contractor rate plus platform fee (about 30%, sacra estimate) pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Revelo or Mercor?
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 provider before shortlisting.
What are the main differences between Revelo and Mercor?
Revelo's primary differentiator is: no upfront fees, no long-term contract and published salary benchmarks. Mercor's primary differentiator is: volume contractor hiring with a percentage platform fee. They also differ in team size (400,000+ network (company figure) vs 300–400 staff; large contractor network), minimum engagement (Not published vs Not published), and primary industries served (Technology, Fintech vs AI labs, Technology).
Verify all details directly with each provider before making a decision.