Quantiphi vs BairesDev: full comparison for 2026
Quick verdict
Quantiphi (4.2/5) edges ahead of BairesDev (3.9/5) overall. Quantiphi is the better choice for procurement teams that want a defined staffing product from a large AI-only firm. BairesDev is the stronger option for U.S. buyers who want AI and software engineers under one nearshore contract. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs BairesDev: head-to-head summary
| Criterion | Quantiphi | BairesDev |
|---|---|---|
| Founded | 2013 | 2009 |
| HQ | Marlborough, Massachusetts, USA | San Francisco, California, USA |
| Team size | 3,000–4,000+ | 4,000+ |
| Rating | 4.2 / 5 | 3.9 / 5 |
| Primary differentiator | Elastic Staffing, a packaged staffing program built with AWS | One contract for mixed AI and software teams in U.S. time zones |
| Pricing model | Elastic Staffing billed per specialist; consulting quoted separately; rates on request | Monthly per engineer or team; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | Healthcare, Financial services, Energy, Retail, Media | Technology, Financial services, Healthcare, Retail, Media |
Quantiphi vs BairesDev: overview
Quantiphi
Quantiphi, founded in 2013 in Marlborough, Massachusetts, employs between 3,000 and 4,000+ people on AI and data work alone. For buyers, its most useful feature is that staffing comes as a named product. Elastic Staffing, built with AWS, places generative AI and ML specialists into client teams, which gives procurement something defined to sign. It is the right call when you need many roles at once. Smaller requests compete with large consulting programs, and rates appear only after scoping.
BairesDev
BairesDev was founded in Buenos Aires in 2009, is headquartered in San Francisco and employs several thousand engineers across Latin America. Buyers can choose staff augmentation, dedicated teams or project delivery, and the AI practice covers ML, data engineering and generative AI. It is a practical choice when one contract needs to cover AI engineers and the software developers around them. As a generalist, though, its AI depth varies by engineer, and rates are not published.
Services and capabilities: Quantiphi vs BairesDev
| Capability | Quantiphi | BairesDev |
|---|---|---|
| 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: Quantiphi vs BairesDev
| Framework / platform | Quantiphi | BairesDev |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Quantiphi vs BairesDev
| Criterion | Quantiphi | BairesDev |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated, Dedicated team, Project delivery | Full-time dedicated, Dedicated team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Quantiphi vs BairesDev
| Dimension | Quantiphi | BairesDev |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Financial services, Energy | Technology, Financial services, Healthcare |
| Best use cases | Buying ten GenAI specialists under one contract, Staffing a SageMaker migration | Staffing a GenAI feature team with supporting developers, Adding data engineers to a nearshore program |
| Typical project type | Full-time dedicated | Full-time dedicated |
Quantiphi vs BairesDev: pros and cons
| Quantiphi | |
|---|---|
| + | A named staffing product simplifies procurement |
| + | Can fill many AI roles at once |
| + | Senior partner status with Google Cloud and AWS |
| - | Small requests get less attention |
| - | No public rates or trial |
| - | Headcount estimates vary |
| BairesDev | |
|---|---|
| + | Large bench in U.S. time zones |
| + | Mixed AI and software teams |
| + | Mature contracting |
| - | AI depth varies |
| - | No public rates |
| - | No published trial |
Who should choose Quantiphi?
A typical fit: buying ten GenAI specialists under one contract.
Elastic Staffing, a packaged staffing program built with AWS. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Energy, Retail, Media.
Who should choose BairesDev?
A typical fit: staffing a GenAI feature team with supporting developers.
One contract for mixed AI and software teams in U.S. time zones. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Financial services, Healthcare, Retail, Media.
Decision matrix: Quantiphi vs BairesDev
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Both; Quantiphi 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 | Neither publishes rates; ask both for a written rate card |
| Your budget is at the lower end | Compare: Quantiphi (Not published) vs BairesDev (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 | Both; Quantiphi rates higher overall |
Use case fit: Quantiphi vs BairesDev
| Use case | Quantiphi fit | BairesDev fit | Winner |
|---|---|---|---|
| Buying ten GenAI specialists under one contract | Strong | Limited | Quantiphi |
| Staffing a SageMaker migration | Strong | Strong | Both equally |
| Staffing a GenAI feature team with supporting developers | Strong | Strong | Both equally |
| Adding data engineers to a nearshore program | Strong | Strong | Both equally |
Verdict: Quantiphi vs BairesDev
Quantiphi (4.2/5) is the stronger overall choice for most AI Staff Augmentation projects. Elastic Staffing, a packaged staffing program built with AWS.
BairesDev (3.9/5) is worth a look if you need adding data engineers to a nearshore program. If your situation matches that, BairesDev is a competitive option.
Related comparisons
Quantiphi vs BairesDev FAQ
Is Quantiphi better than BairesDev?
Quantiphi (4.2/5) scores higher overall, but "better" depends on your use case. Quantiphi's strongest advantage: a named staffing product simplifies procurement. BairesDev's strongest advantage: large bench in U.S. time zones.
How do Quantiphi and BairesDev differ in pricing?
Quantiphi uses elastic staffing billed per specialist; consulting quoted separately; rates on request pricing. BairesDev uses monthly per engineer or team; 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: Quantiphi or BairesDev?
Quantiphi 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 Quantiphi and BairesDev?
Quantiphi's primary differentiator is: elastic Staffing, a packaged staffing program built with AWS. BairesDev's primary differentiator is: one contract for mixed AI and software teams in U.S. time zones. They also differ in team size (3,000–4,000+ vs 4,000+), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Financial services vs Technology, Financial services).
Verify all details directly with each provider before making a decision.