deepsense.ai vs ScienceSoft: full comparison for 2026
Quick verdict
deepsense.ai (4.3/5) edges ahead of ScienceSoft (3.7/5) overall. deepsense.ai is the better choice for research-heavy ML problems, computer vision, edge AI. ScienceSoft is the stronger option for regulated companies wanting a documented hiring process. The right choice depends on your project size, budget, and required tech stack.
deepsense.ai vs ScienceSoft: head-to-head summary
| Criterion | deepsense.ai | ScienceSoft |
|---|---|---|
| Founded | 2014 | 1989 |
| HQ | Warsaw, Poland | McKinney, Texas, USA |
| Team size | 100–200 | 750+ |
| Rating | 4.3 / 5 | 3.7 / 5 |
| Primary differentiator | A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench | Publishes its staff augmentation timeline and process |
| Pricing model | Time and materials for augmented engineers; project contracts; rates on request | Hourly or monthly rates shared with CVs; time and materials |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Azure ML, AWS |
| Industries served | Manufacturing, Retail & e-commerce, Healthcare & life sciences, Financial services, Software & SaaS | Healthcare & life sciences, Financial services, Manufacturing, Retail & e-commerce |
deepsense.ai vs ScienceSoft: overview
deepsense.ai
deepsense.ai was founded in 2014, grew out of the AI division of CodiLime, and is headquartered in Warsaw with an office in Palo Alto. Third-party directories put its headcount between roughly 100 and 200 people, and the company says it employs more than 120 AI experts, including Kaggle competition winners and PhD holders. Besides project work in generative AI, MLOps, computer vision and edge AI, it runs a dedicated AI staff augmentation service in which its own engineers extend a client's team.
ScienceSoft
ScienceSoft dates its IT work to 1989 and is headquartered in McKinney, Texas. It says its staff augmentation pool covers more than 750 professionals, including data scientists with long industry experience, and it publishes a fast hiring sequence: CVs with rates within a day, interviews in two to four days and starts in one to two weeks (per company website; independently unverifiable). AI is one of many service areas alongside its long-standing healthcare and finance work.
Services and capabilities: deepsense.ai vs ScienceSoft
| Capability | deepsense.ai | ScienceSoft |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✗ |
| MLOps & deployment | ✓ | ✗ |
| Computer vision | ✓ | ✗ |
| Data engineering | ✗ | ✓ |
| AI agent development | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
Tech stack comparison: deepsense.ai vs ScienceSoft
| Framework / platform | deepsense.ai | ScienceSoft |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Databricks | N/A | N/A |
| MLflow | ✓ | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: deepsense.ai vs ScienceSoft
| Criterion | deepsense.ai | ScienceSoft |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: deepsense.ai vs ScienceSoft
| Dimension | deepsense.ai | ScienceSoft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail & e-commerce, Healthcare & life sciences | Healthcare & life sciences, Financial services, Manufacturing |
| Best use cases | Adding a computer-vision specialist to a manufacturing quality team, Bringing research depth into a stalled model-accuracy effort | Adding a data scientist to a healthcare analytics team, Staffing BI and ML roles for a manufacturer |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
deepsense.ai vs ScienceSoft: pros and cons
| deepsense.ai | |
|---|---|
| + | Every engineer it places comes from an AI-only company |
| + | Strong record in computer vision and edge deployment |
| + | Clutch reviewers describe team-augmentation work with strong engineering skills |
| - | A bench of roughly 120 AI staff limits how many people can start at once |
| - | Polish rates are higher than Ukrainian or Latin American alternatives |
| - | Better suited to hard modeling work than to routine LLM integration |
| ScienceSoft | |
|---|---|
| + | Shares rates together with candidate CVs |
| + | Long history in healthcare and finance |
| + | Clear published hiring timeline |
| - | AI is a small part of a very wide catalog |
| - | Fewer GenAI specialists than AI-focused firms |
| - | Speed figures come from its own marketing |
Who should choose deepsense.ai?
A typical fit: adding a computer-vision specialist to a manufacturing quality team.
A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail & e-commerce, Healthcare & life sciences, Financial services, Software & SaaS.
Who should choose ScienceSoft?
A typical fit: adding a data scientist to a healthcare analytics team.
Publishes its staff augmentation timeline and process. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare & life sciences, Financial services, Manufacturing, Retail & e-commerce.
Decision matrix: deepsense.ai vs ScienceSoft
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; deepsense.ai rates higher overall |
| You want the supplier to own delivery as well as staffing | deepsense.ai |
| You need one expert part-time | Neither lists part-time experts; ask about reduced hours |
| You want to test an engineer before signing for months | Neither publishes a trial; ask for a short first term |
| Your budget is at the lower end | Compare: deepsense.ai (Not published) vs ScienceSoft (Not published) |
| You need overlap with U.S. working hours | Neither is nearshore; agree overlap hours up front |
| You need specialist depth in a specific vertical | deepsense.ai |
Use case fit: deepsense.ai vs ScienceSoft
| Use case | deepsense.ai fit | ScienceSoft fit | Winner |
|---|---|---|---|
| Adding a computer-vision specialist to a manufacturing quality team | Strong | Strong | Both equally |
| Bringing research depth into a stalled model-accuracy effort | Strong | Limited | deepsense.ai |
| Adding a data scientist to a healthcare analytics team | Strong | Strong | Both equally |
| Staffing BI and ML roles for a manufacturer | Limited | Strong | ScienceSoft |
Verdict: deepsense.ai vs ScienceSoft
deepsense.ai (4.3/5) is the stronger overall choice for most AI Staff Augmentation projects. A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench.
ScienceSoft (3.7/5) is worth a look if you need staffing BI and ML roles for a manufacturer. If your situation matches that, ScienceSoft is a competitive option.
Related comparisons
deepsense.ai vs ScienceSoft FAQ
Is deepsense.ai better than ScienceSoft?
deepsense.ai (4.3/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: every engineer it places comes from an AI-only company. ScienceSoft's strongest advantage: shares rates together with candidate CVs.
How do deepsense.ai and ScienceSoft differ in pricing?
deepsense.ai uses time and materials for augmented engineers; project contracts; rates on request pricing. ScienceSoft uses hourly or monthly rates shared with cvs; time and materials 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 ScienceSoft?
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 company before shortlisting.
What are the main differences between deepsense.ai and ScienceSoft?
deepsense.ai's primary differentiator is: a pure applied-AI firm whose augmented engineers come from a research-grade data-science bench. ScienceSoft's primary differentiator is: publishes its staff augmentation timeline and process. They also differ in team size (100–200 vs 750+), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Retail & e-commerce vs Healthcare & life sciences, Financial services).
Verify all details directly with each company before making a decision.