deepsense.ai vs Data Science UA: full comparison for 2026
Quick verdict
deepsense.ai (4.4/5) edges ahead of Data Science UA (3.8/5) overall. deepsense.ai is the better choice for long monthly contracts with employed senior ML engineers. Data Science UA is the stronger option for companies that want to choose between a recruiting fee and monthly outstaffing for Ukrainian AI talent. The right choice depends on your project size, budget, and required tech stack.
deepsense.ai vs Data Science UA: head-to-head summary
| Criterion | deepsense.ai | Data Science UA |
|---|---|---|
| Founded | 2014 | 2016 |
| HQ | Warsaw, Poland | Kyiv, Ukraine (legal HQ London) |
| Team size | 100–200 | 50–200 |
| Rating | 4.4 / 5 | 3.8 / 5 |
| Primary differentiator | Monthly access to about 120 employed AI specialists with production experience | Recruiting fee or monthly outstaffing from an AI-only recruiter |
| Pricing model | Team extension billed monthly per engineer; projects quoted separately; rates on request | Recruiting fee per hire; outstaffing billed monthly; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, PyTorch, TensorFlow |
| Industries served | Manufacturing, Retail, Healthcare, Financial services, Technology | Technology, Fintech, Healthcare, Retail, Gaming |
deepsense.ai vs Data Science UA: overview
deepsense.ai
deepsense.ai has worked on AI from Warsaw since 2014 and employs about 120 AI specialists, according to its job listings. You buy its engineers as monthly team extension, alongside or instead of a consulting project, and most of them are employees rather than contractors, which keeps the same person on your work for longer. Its strengths are computer vision, MLOps and LLM systems that have to run in production. There is no public rate card, and staffing gets less marketing attention than its project work.
Data Science UA
Data Science UA grew out of a 2016 data science conference in Kyiv and now runs recruiting, outstaffing and AI consulting, with a legal base in London. It offers two ways to buy. You can pay a recruiting fee for a permanent hire, which it says takes two to four weeks on average, or take the engineer on monthly outstaffing terms first. Its AI community, quoted at 10,000 to 30,000 people, gives it reach. Screening is done by recruiters, so plan your own technical interview.
Services and capabilities: deepsense.ai vs Data Science UA
| Capability | deepsense.ai | Data Science UA |
|---|---|---|
| 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: deepsense.ai vs Data Science UA
| Framework / platform | deepsense.ai | Data Science UA |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: deepsense.ai vs Data Science UA
| Criterion | deepsense.ai | Data Science UA |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated, Dedicated team, Project delivery | Direct hire, Full-time dedicated, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: deepsense.ai vs Data Science UA
| Dimension | deepsense.ai | Data Science UA |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail, Healthcare | Technology, Fintech, Healthcare |
| Best use cases | Extending a platform team with an MLOps engineer for a year, Adding a computer vision engineer to a quality-inspection product | Hiring a permanent ML engineer in Ukraine, Outstaffing a computer vision engineer before a permanent offer |
| Typical project type | Full-time dedicated | Direct hire |
deepsense.ai vs Data Science UA: pros and cons
| deepsense.ai | |
|---|---|
| + | Mostly employed engineers, so continuity is good |
| + | Can switch between staffing and a delivered project |
| + | Strong computer vision and MLOps depth |
| - | No part-time or trial option published |
| - | No public rates |
| - | About 120 people, so large requests take time |
| Data Science UA | |
|---|---|
| + | Both recruiting and outstaffing |
| + | Recruiters focused on AI roles |
| + | Large Ukrainian AI community |
| - | Recruiter-led screening |
| - | Size and headquarters vary by source |
| - | Wartime continuity risk |
Who should choose deepsense.ai?
A typical fit: extending a platform team with an MLOps engineer for a year.
Monthly access to about 120 employed AI specialists with production experience. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail, Healthcare, Financial services, Technology.
Who should choose Data Science UA?
A typical fit: hiring a permanent ML engineer in Ukraine.
Recruiting fee or monthly outstaffing from an AI-only recruiter. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Fintech, Healthcare, Retail, Gaming.
Decision matrix: deepsense.ai vs Data Science UA
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Both; deepsense.ai 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: deepsense.ai (Not published) vs Data Science UA (Not published) |
| You may want to hire the engineer permanently later | Data Science UA |
| You want several engineers working as one team | Both; deepsense.ai rates higher overall |
Use case fit: deepsense.ai vs Data Science UA
| Use case | deepsense.ai fit | Data Science UA fit | Winner |
|---|---|---|---|
| Extending a platform team with an MLOps engineer for a year | Strong | Limited | deepsense.ai |
| Adding a computer vision engineer to a quality-inspection product | Strong | Limited | deepsense.ai |
| Hiring a permanent ML engineer in Ukraine | Limited | Strong | Data Science UA |
| Outstaffing a computer vision engineer before a permanent offer | Limited | Strong | Data Science UA |
Verdict: deepsense.ai vs Data Science UA
deepsense.ai (4.4/5) is the stronger overall choice for most AI Staff Augmentation projects. Monthly access to about 120 employed AI specialists with production experience.
Data Science UA (3.8/5) is worth a look if you need outstaffing a computer vision engineer before a permanent offer. If your situation matches that, Data Science UA is a competitive option.
Related comparisons
deepsense.ai vs Data Science UA FAQ
Is deepsense.ai better than Data Science UA?
deepsense.ai (4.4/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: mostly employed engineers, so continuity is good. Data Science UA's strongest advantage: both recruiting and outstaffing.
How do deepsense.ai and Data Science UA differ in pricing?
deepsense.ai uses team extension billed monthly per engineer; projects quoted separately; rates on request pricing. Data Science UA uses recruiting fee per hire; outstaffing billed monthly; 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: deepsense.ai or Data Science UA?
deepsense.ai 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 deepsense.ai and Data Science UA?
deepsense.ai's primary differentiator is: monthly access to about 120 employed AI specialists with production experience. Data Science UA's primary differentiator is: recruiting fee or monthly outstaffing from an AI-only recruiter. They also differ in team size (100–200 vs 50–200), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Retail vs Technology, Fintech).
Verify all details directly with each provider before making a decision.