Quantiphi vs Azumo: full comparison for 2026
Quick verdict
Quantiphi (4.3/5) edges ahead of Azumo (3.9/5) overall. Quantiphi is the better choice for enterprises that need many AI roles filled at once by one AI-only supplier. Azumo is the stronger option for U.S. teams on a tight budget that need ML engineers who work their hours. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs Azumo: head-to-head summary
| Criterion | Quantiphi | Azumo |
|---|---|---|
| Founded | 2013 | 2016 |
| HQ | Marlborough, Massachusetts, USA | San Francisco, California, USA |
| Team size | 3,000–4,000+ | 50–249 |
| Rating | 4.3 / 5 | 3.9 / 5 |
| Primary differentiator | The biggest AI-only bench here, sold through a named staffing program with AWS | The lowest published hourly band on this page with full U.S. time-zone overlap |
| Pricing model | Elastic Staffing billed per specialist; consulting quoted separately; rates on request | $25–$49/hr (Clutch band); monthly staff augmentation or dedicated team |
| Min. engagement | Not published | $10,000+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, PyTorch, TensorFlow |
| Industries served | Healthcare, Financial services, Energy, Retail, Media | SaaS, Fintech, Healthcare, Retail, Media |
Quantiphi vs Azumo: overview
Quantiphi
Quantiphi, based in Marlborough, Massachusetts and founded in 2013, is the largest company on this page that works only on AI and data, with directory estimates between 3,000 and more than 4,000 people. Its Elastic Staffing program, built with AWS, places generative AI and ML specialists into client teams. That scale is the reason it ranks here: no other AI-only supplier can staff ML, MLOps, data and LLM roles in parallel. Google Cloud named it 2025 AI Partner of the Year for North America. The cost is attention, since staffing is one product inside a large consulting business.
Azumo
Azumo was founded in 2016, is headquartered in San Francisco and delivers mostly from Argentina, with an office in Rosario. Clutch lists an hourly band of $25 to $49 and a $10,000 minimum project, the lowest published rate on this page. It offers staff augmentation, dedicated nearshore teams and virtual CTO services, and it won a Clutch award as a top AI developer in 2023. Its engineers keep U.S. hours, so daily stand-ups are easy. The catch is depth. AI is a strong practice but one of several, and specialist experience varies by role.
Services and capabilities: Quantiphi vs Azumo
| Capability | Quantiphi | Azumo |
|---|---|---|
| ML engineers | ✓ | ✓ |
| LLM / GenAI engineers | ✓ | ✓ |
| AI agent developers | ✗ | ✗ |
| MLOps engineers | ✓ | ✗ |
| Computer vision engineers | ✓ | ✗ |
| NLP engineers | ✗ | ✗ |
| Data engineers | ✓ | ✓ |
| Engineer-led technical screen | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✓ |
| Direct hire option | ✗ | ✗ |
Tech stack comparison: Quantiphi vs Azumo
| Framework / platform | Quantiphi | Azumo |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Quantiphi vs Azumo
| Criterion | Quantiphi | Azumo |
|---|---|---|
| Minimum engagement | Not published | $10,000+ |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Dedicated engineer, Dedicated team, Project delivery |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Accessible |
Target audience comparison: Quantiphi vs Azumo
| Dimension | Quantiphi | Azumo |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Financial services, Energy | SaaS, Fintech, Healthcare |
| Best use cases | Staffing eight GenAI specialists into an enterprise program, Adding Vertex AI or SageMaker engineers for a cloud ML migration | Adding a nearshore LLM engineer to a U.S. SaaS team, Building a data engineering squad on a startup budget |
| Typical project type | Dedicated engineer | Dedicated engineer |
Quantiphi vs Azumo: pros and cons
| Quantiphi | |
|---|---|
| + | Can staff several AI specialties in parallel, which no other AI-only firm here can |
| + | Top partner tiers with Google Cloud and AWS help on cloud-specific ML roles |
| + | A named staffing product makes procurement simpler |
| - | Requests for one or two engineers compete with large consulting programs |
| - | Rates appear only after scoping |
| - | Headcount estimates vary widely between sources |
| Azumo | |
|---|---|
| + | Published hourly band is the lowest on this list |
| + | Argentina shares working hours with U.S. teams |
| + | Clutch cost rating of 4.8 |
| - | AI is one of several practices, not the whole company |
| - | Fewer research-grade ML specialists than AI-only firms |
| - | Team size reported between 50 and 500 depending on the source |
Who should choose Quantiphi?
A typical fit: staffing eight GenAI specialists into an enterprise program.
The biggest AI-only bench here, sold through a named staffing program with AWS. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Energy, Retail, Media.
Who should choose Azumo?
A typical fit: adding a nearshore LLM engineer to a U.S. SaaS team.
The lowest published hourly band on this page with full U.S. time-zone overlap. Minimum engagement starts at $10,000+. Works best with clients in SaaS, Fintech, Healthcare, Retail, Media.
Decision matrix: Quantiphi vs Azumo
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Neither documents an engineer-led screen; run your own technical interview |
| You need one specialist for a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Both; Quantiphi rates higher overall |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| Your budget is at the lower end | Compare: Quantiphi (Not published) vs Azumo ($10,000+) |
| Your team works U.S. hours | Azumo |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
Use case fit: Quantiphi vs Azumo
| Use case | Quantiphi fit | Azumo fit | Winner |
|---|---|---|---|
| Staffing eight GenAI specialists into an enterprise program | Strong | Strong | Both equally |
| Adding Vertex AI or SageMaker engineers for a cloud ML migration | Strong | Strong | Both equally |
| Adding a nearshore LLM engineer to a U.S. SaaS team | Strong | Strong | Both equally |
| Building a data engineering squad on a startup budget | Limited | Strong | Azumo |
Verdict: Quantiphi vs Azumo
Quantiphi (4.3/5) is the stronger overall choice for most AI Engineer Staffing projects. The biggest AI-only bench here, sold through a named staffing program with AWS.
Azumo (3.9/5) is worth a look if you need building a data engineering squad on a startup budget. If your situation matches that, Azumo is a competitive option.
Related comparisons
Quantiphi vs Azumo FAQ
Is Quantiphi better than Azumo?
Quantiphi (4.3/5) scores higher overall, but "better" depends on your use case. Quantiphi's strongest advantage: can staff several AI specialties in parallel, which no other AI-only firm here can. Azumo's strongest advantage: published hourly band is the lowest on this list.
How do Quantiphi and Azumo differ in pricing?
Quantiphi uses elastic staffing billed per specialist; consulting quoted separately; rates on request pricing. Azumo uses $25–$49/hr (clutch band); monthly staff augmentation or dedicated team pricing with a minimum engagement of $10,000+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Quantiphi or Azumo?
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 company before shortlisting.
What are the main differences between Quantiphi and Azumo?
Quantiphi's primary differentiator is: the biggest AI-only bench here, sold through a named staffing program with AWS. Azumo's primary differentiator is: the lowest published hourly band on this page with full U.S. time-zone overlap. They also differ in team size (3,000–4,000+ vs 50–249), minimum engagement (Not published vs $10,000+), and primary industries served (Healthcare, Financial services vs SaaS, Fintech).
Verify all details directly with each company before making a decision.