Tensorway vs ScienceSoft: full comparison for 2026
Quick verdict
Tensorway (4.8/5) edges ahead of ScienceSoft (4.0/5) overall. Tensorway is the better choice for product teams adding AI engineers fast, two-week trial. ScienceSoft is the stronger option for regulated industries hiring experienced data scientists. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs ScienceSoft: head-to-head summary
| Criterion | Tensorway | ScienceSoft |
|---|---|---|
| Founded | 2019 | 1989 |
| HQ | Alicante, Spain | McKinney, Texas, USA |
| Team size | 50–249 | 750+ |
| Rating | 4.8 / 5 | 4.0 / 5 |
| Primary differentiator | Engineer-led screening with a free replacement if a hire doesn't fit | Senior data scientists with a published hiring timeline |
| Pricing model | Monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request | Time and materials; rates sent with CVs |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | PyTorch, TensorFlow, LangChain | Python, R, Azure ML |
| Industries served | Healthcare, Legal services, SaaS, Fintech, E-commerce and retail, Manufacturing, Logistics | Healthcare, Manufacturing, Fintech, Retail |
Tensorway vs ScienceSoft: overview
Tensorway
Tensorway is an AI engineering company founded in 2019 and based in Alicante, Spain, with more than 20 years of software engineering experience in its leadership and delivery processes. Its staff-augmentation service places ML engineers, LLM engineers, AI agent developers, MLOps engineers, computer-vision and NLP specialists, data engineers and RAG specialists directly into a client's own team, where they work in the client's Slack, Jira and repositories. Candidates are screened by senior AI engineers through a code review, a practical task in their specialization and a communication check, so the client receives a shortlist of two or three people that is already technically vetted. Tensorway handles contracts and admin; the first engineer typically starts within one to two weeks and a full squad within three to four weeks (per company website; independently unverifiable). One published case study describes a U.S. law practice, Liner Legal, cutting medical-record processing from about a week to 5–15 minutes (per company website; independently unverifiable).
ScienceSoft
ScienceSoft dates its IT work to 1989 and is headquartered in McKinney, Texas, with representative offices in the UAE, Saudi Arabia, Europe and Mexico. Its staff-augmentation pool covers more than 750 professionals, including data scientists with 7–20 years of experience. The company says it sends CVs with rates within 24 hours, arranges interviews in two to four days and has people starting within one to two weeks (per company website; independently unverifiable).
Services and capabilities: Tensorway vs ScienceSoft
| Capability | Tensorway | 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: Tensorway vs ScienceSoft
| Framework / platform | Tensorway | ScienceSoft |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | N/A |
| AWS SageMaker | N/A | ✓ |
| Azure ML | N/A | ✓ |
| Databricks | N/A | N/A |
| MLflow | ✓ | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Tensorway vs ScienceSoft
| Criterion | Tensorway | ScienceSoft |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Part-time fractional experts, Trial period | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Tensorway vs ScienceSoft
| Dimension | Tensorway | ScienceSoft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Legal services, SaaS | Healthcare, Manufacturing, Fintech |
| Best use cases | Adding an LLM engineer and a RAG specialist to an existing SaaS product team, Trialing a single ML engineer for two weeks before committing to a monthly contract | Adding a senior data scientist to a healthcare analytics team, Staffing a manufacturing predictive-maintenance project |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
Tensorway vs ScienceSoft: pros and cons
| Tensorway | |
|---|---|
| + | Candidates are screened by working AI engineers through a code review and a practical task, so your interviews can focus on team fit |
| + | A shortlist of two or three people usually arrives within a week of the discovery call |
| + | A poor fit is replaced at no cost, and the monthly commitment can be adjusted between sprints |
| + | All code, documentation and trained models stay in your repositories, which keeps vendor lock-in off the table |
| + | Contracts, local employment paperwork and benefits admin are handled by Tensorway rather than your HR team |
| - | No public rate card, so budgeting starts with a sales call |
| - | The bench is far smaller than the large talent networks, which matters if you need ten or more engineers at once |
| - | AI and ML roles only; general full-stack or QA staffing is out of scope |
| - | Time-zone overlap is arranged per engagement instead of guaranteed by a fixed nearshore location |
| ScienceSoft | |
|---|---|
| + | Rates arrive with the CVs, before any sales calls |
| + | Long history in healthcare and manufacturing IT |
| + | Experienced data scientists rather than junior ML hires |
| - | AI is one of many service lines |
| - | Smaller bench than the large nearshore firms |
| - | Headcount figures differ between the company's own pages |
Who should choose Tensorway?
A typical fit: adding an LLM engineer and a RAG specialist to an existing SaaS product team.
Engineer-led screening with a free replacement if a hire doesn't fit. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Legal services, SaaS, Fintech, E-commerce and retail, Manufacturing, Logistics.
Who should choose ScienceSoft?
A typical fit: adding a senior data scientist to a healthcare analytics team.
Senior data scientists with a published hiring timeline. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Manufacturing, Fintech, Retail.
Decision matrix: Tensorway vs ScienceSoft
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Tensorway |
| Your budget is at the lower end | Compare: Tensorway (Not disclosed) vs ScienceSoft (Not disclosed) |
| You need specialist depth in a specific vertical | Tensorway |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: Tensorway vs ScienceSoft
| Use case | Tensorway fit | ScienceSoft fit | Winner |
|---|---|---|---|
| Adding an LLM engineer and a RAG specialist to an existing SaaS product team | Strong | Strong | Both equally |
| Trialing a single ML engineer for two weeks before committing to a monthly contract | Strong | Limited | Tensorway |
| Adding a senior data scientist to a healthcare analytics team | Strong | Strong | Both equally |
| Staffing a manufacturing predictive-maintenance project | Strong | Strong | Both equally |
Verdict: Tensorway vs ScienceSoft
Tensorway (4.8/5) is the stronger overall choice for most AI Staffing projects. Engineer-led screening with a free replacement if a hire doesn't fit.
ScienceSoft (4.0/5) is worth a look if you need staffing a manufacturing predictive-maintenance project. If your situation matches that, ScienceSoft is a competitive option.
Related comparisons
Tensorway vs ScienceSoft FAQ
Is Tensorway better than ScienceSoft?
Tensorway (4.8/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: candidates are screened by working AI engineers through a code review and a practical task, so your interviews can focus on team fit. ScienceSoft's strongest advantage: rates arrive with the CVs, before any sales calls.
How do Tensorway and ScienceSoft differ in pricing?
Tensorway uses monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request pricing. ScienceSoft uses time and materials; rates sent with cvs pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or ScienceSoft?
Tensorway is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Tensorway and ScienceSoft?
Tensorway's primary differentiator is: engineer-led screening with a free replacement if a hire doesn't fit. ScienceSoft's primary differentiator is: senior data scientists with a published hiring timeline. They also differ in team size (50–249 vs 750+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthcare, Legal services vs Healthcare, Manufacturing).
Verify all details directly with each agency before making a decision.