Azumo vs Pento: full comparison for 2026
Quick verdict
Azumo (4.3/5) edges ahead of Pento (4.0/5) overall. Azumo is the better choice for U.S. buyers who need the lowest published rate with same-day overlap. Pento is the stronger option for U.S. teams that want a nearshore ML engineer at a known mid-range rate. The right choice depends on your project size, budget, and required tech stack.
Azumo vs Pento: head-to-head summary
| Criterion | Azumo | Pento |
|---|---|---|
| Founded | 2016 | 2019 |
| HQ | San Francisco, California, USA | Montevideo, Uruguay |
| Team size | 50–249 | 10–49 |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | A $25–$49 Clutch band with engineers working U.S. hours | Published mid-range rate with close U.S. Eastern overlap |
| Pricing model | $25–$49/hr (Clutch band); staff augmentation or dedicated team; no long-term commitment (per company) | $50–$99/hr (Clutch band); augmentation or project delivery |
| Min. engagement | $10,000+ | $25,000+ |
| Primary tech stack | Python, PyTorch, OpenAI | Python, PyTorch, scikit-learn |
| Industries served | SaaS, Fintech, Healthcare, Retail, Media | Retail, Fintech, SaaS, Logistics, Media |
Azumo vs Pento: overview
Azumo
Azumo was founded in 2016, is headquartered in San Francisco and delivers mostly from Argentina, including an office in Rosario. On Clutch its hourly band is $25 to $49, with a $10,000 minimum project, which makes it the cheapest provider on this page that publishes a figure. You can buy single engineers through staff augmentation, a dedicated nearshore team or virtual CTO services, all without a long-term commitment, according to its site. AI is one of several practices, so check the experience of each engineer you are offered.
Pento
Pento is a Montevideo company with 10 to 49 people that designs, builds and deploys machine learning systems for mid-market and enterprise clients. Clutch shows an hourly band of $50 to $99 and a $25,000 minimum project, so you can budget before the first call. It describes its work as either augmenting internal teams or delivering whole systems. Uruguay's working day overlaps closely with U.S. Eastern time. The small team means one or two engineers at a time.
Services and capabilities: Azumo vs Pento
| Capability | Azumo | Pento |
|---|---|---|
| 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: Azumo vs Pento
| Framework / platform | Azumo | Pento |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | ✓ |
| Databricks | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Azumo vs Pento
| Criterion | Azumo | Pento |
|---|---|---|
| Minimum engagement | $10,000+ | $25,000+ |
| Engagement models | Full-time dedicated, Dedicated team, Project delivery | Full-time dedicated, Project delivery |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Mid-market |
Target audience comparison: Azumo vs Pento
| Dimension | Azumo | Pento |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Healthcare | Retail, Fintech, SaaS |
| Best use cases | Adding a nearshore LLM engineer on a startup budget, Building a chatbot squad that joins U.S. stand-ups | Adding a forecasting specialist to a retail team, Building an anomaly-detection model with nearshore help |
| Typical project type | Full-time dedicated | Full-time dedicated |
Azumo vs Pento: pros and cons
| Azumo | |
|---|---|
| + | Lowest published band on this list |
| + | U.S. time-zone overlap |
| + | No long-term commitment required |
| - | AI is one practice among several |
| - | Fewer research-grade ML specialists |
| - | Headcount varies widely by source |
| Pento | |
|---|---|
| + | Rate band and minimum are public |
| + | Close overlap with U.S. Eastern time |
| + | Focused on ML systems, not general software |
| - | Very small team |
| - | Highest published minimum on this list |
| - | Few public reviews |
Who should choose Azumo?
A typical fit: adding a nearshore LLM engineer on a startup budget.
A $25–$49 Clutch band with engineers working U.S. hours. Minimum engagement starts at $10,000+. Works best with clients in SaaS, Fintech, Healthcare, Retail, Media.
Who should choose Pento?
A typical fit: adding a forecasting specialist to a retail team.
Published mid-range rate with close U.S. Eastern overlap. Minimum engagement starts at $25,000+. Works best with clients in Retail, Fintech, SaaS, Logistics, Media.
Decision matrix: Azumo vs Pento
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Both; Azumo 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 | Both; Azumo rates higher overall |
| Your budget is at the lower end | Azumo |
| 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 | Azumo |
Use case fit: Azumo vs Pento
| Use case | Azumo fit | Pento fit | Winner |
|---|---|---|---|
| Adding a nearshore LLM engineer on a startup budget | Strong | Strong | Both equally |
| Building a chatbot squad that joins U.S. stand-ups | Strong | Strong | Both equally |
| Adding a forecasting specialist to a retail team | Strong | Strong | Both equally |
| Building an anomaly-detection model with nearshore help | Strong | Strong | Both equally |
Verdict: Azumo vs Pento
Azumo (4.3/5) is the stronger overall choice for most AI Staff Augmentation projects. A $25–$49 Clutch band with engineers working U.S. hours.
Pento (4.0/5) is worth a look if you need building an anomaly-detection model with nearshore help. If your situation matches that, Pento is a competitive option.
Related comparisons
Azumo vs Pento FAQ
Is Azumo better than Pento?
Azumo (4.3/5) scores higher overall, but "better" depends on your use case. Azumo's strongest advantage: lowest published band on this list. Pento's strongest advantage: rate band and minimum are public.
How do Azumo and Pento differ in pricing?
Azumo uses $25–$49/hr (clutch band); staff augmentation or dedicated team; no long-term commitment (per company) pricing with a minimum engagement of $10,000+. Pento uses $50–$99/hr (clutch band); augmentation or project delivery pricing with a minimum engagement of $25,000+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Azumo or Pento?
Azumo 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 Azumo and Pento?
Azumo's primary differentiator is: a $25–$49 Clutch band with engineers working U.S. hours. Pento's primary differentiator is: published mid-range rate with close U.S. Eastern overlap. They also differ in team size (50–249 vs 10–49), minimum engagement ($10,000+ vs $25,000+), and primary industries served (SaaS, Fintech vs Retail, Fintech).
Verify all details directly with each provider before making a decision.