Vstorm vs Revelo: full comparison for 2026
Quick verdict
Vstorm (4.2/5) edges ahead of Revelo (4.0/5) overall. Vstorm is the better choice for agent engineering bought at a known rate and minimum. Revelo is the stronger option for U.S. companies that want a Latin American AI engineer without upfront fees or a long contract. The right choice depends on your project size, budget, and required tech stack.
Vstorm vs Revelo: head-to-head summary
| Criterion | Vstorm | Revelo |
|---|---|---|
| Founded | 2017 | 2014 |
| HQ | Wrocław, Poland | Miami, Florida, USA |
| Team size | 10–49 | 400,000+ network (company figure) |
| Rating | 4.2 / 5 | 4.0 / 5 |
| Primary differentiator | Published rate and minimum for specialist agent engineers | No upfront fees, no long-term contract and published salary benchmarks |
| Pricing model | $100–$149/hr (Clutch band); team extension or project billing | Monthly per engineer; no upfront fees or long-term contracts (per company); senior AI/ML all-in cost about $103,000/yr (company benchmark) |
| Min. engagement | $10,000+ | Not published |
| Primary tech stack | Python, LangChain, LlamaIndex | Python, PyTorch, TensorFlow |
| Industries served | SaaS, Legal, Financial services, Healthcare, Retail | Technology, Fintech, SaaS, Healthcare, AI labs |
Vstorm vs Revelo: overview
Vstorm
Vstorm, in Wrocław since 2017, builds LLM agents and retrieval-augmented systems and lends the same engineers to client teams. Its Clutch profile gives buyers the two numbers most providers hide: an hourly band of $100 to $149 and a $10,000 minimum project. The score from verified reviews is 4.9. With 10 to 49 people, it can supply one or two engineers, not a department, and its work is concentrated on agents rather than classic ML.
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.
Services and capabilities: Vstorm vs Revelo
| Capability | Vstorm | Revelo |
|---|---|---|
| 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: Vstorm vs Revelo
| Framework / platform | Vstorm | Revelo |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | ✓ |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | ✓ |
| Databricks | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Vstorm vs Revelo
| Criterion | Vstorm | Revelo |
|---|---|---|
| Minimum engagement | $10,000+ | Not published |
| Engagement models | Full-time dedicated, Dedicated team, Project delivery | Full-time dedicated, Freelance contract |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Vstorm vs Revelo
| Dimension | Vstorm | Revelo |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Legal, Financial services | Technology, Fintech, SaaS |
| Best use cases | Hiring an agent engineer to fix multi-step tool calls, Adding a RAG specialist for a legal search product | Hiring a Brazilian ML engineer without a long contract, Budgeting a nearshore AI team from published salary data |
| Typical project type | Full-time dedicated | Full-time dedicated |
Vstorm vs Revelo: pros and cons
| Vstorm | |
|---|---|
| + | Rate band and minimum are public |
| + | Agent and RAG specialists |
| + | 4.9 score from verified Clutch reviews |
| - | Small team |
| - | Higher rate than most Central European providers |
| - | Little classic ML or computer vision |
| 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 |
Who should choose Vstorm?
A typical fit: hiring an agent engineer to fix multi-step tool calls.
Published rate and minimum for specialist agent engineers. Minimum engagement starts at $10,000+. Works best with clients in SaaS, Legal, Financial services, Healthcare, Retail.
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.
Decision matrix: Vstorm vs Revelo
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Both; Vstorm rates higher overall |
| 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 | Vstorm |
| Your budget is at the lower end | Compare: Vstorm ($10,000+) vs Revelo (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: Vstorm vs Revelo
| Use case | Vstorm fit | Revelo fit | Winner |
|---|---|---|---|
| Hiring an agent engineer to fix multi-step tool calls | Strong | Strong | Both equally |
| Adding a RAG specialist for a legal search product | Strong | Strong | Both equally |
| Hiring a Brazilian ML engineer without a long contract | Strong | Strong | Both equally |
| Budgeting a nearshore AI team from published salary data | Limited | Strong | Revelo |
Verdict: Vstorm vs Revelo
Vstorm (4.2/5) is the stronger overall choice for most AI Staff Augmentation projects. Published rate and minimum for specialist agent engineers.
Revelo (4.0/5) is worth a look if you need budgeting a nearshore AI team from published salary data. If your situation matches that, Revelo is a competitive option.
Related comparisons
Vstorm vs Revelo FAQ
Is Vstorm better than Revelo?
Vstorm (4.2/5) scores higher overall, but "better" depends on your use case. Vstorm's strongest advantage: rate band and minimum are public. Revelo's strongest advantage: no upfront fee or long-term contract.
How do Vstorm and Revelo differ in pricing?
Vstorm uses $100–$149/hr (clutch band); team extension or project billing pricing with a minimum engagement of $10,000+. 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. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Vstorm or Revelo?
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 Vstorm and Revelo?
Vstorm's primary differentiator is: published rate and minimum for specialist agent engineers. Revelo's primary differentiator is: no upfront fees, no long-term contract and published salary benchmarks. They also differ in team size (10–49 vs 400,000+ network (company figure)), minimum engagement ($10,000+ vs Not published), and primary industries served (SaaS, Legal vs Technology, Fintech).
Verify all details directly with each provider before making a decision.