SoftServe vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
SoftServe (4.0/5) edges ahead of DataArt (3.9/5) overall. SoftServe is the better choice for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices.. DataArt is the stronger option for regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks.. The right choice depends on your project size, budget, and required tech stack.
SoftServe vs DataArt: head-to-head summary
| Criterion | SoftServe | DataArt |
|---|---|---|
| Founded | 1993 | 1997 |
| HQ | Austin, Texas, United States / Lviv, Ukraine | New York, New York, United States |
| Team size | 12,000+ | 6,000+ |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Best for | Enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices. | Regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks. |
| Pricing model | Time & materials, managed engagement | Time & materials, managed engagement |
| Min. engagement | Not published | Not published |
| Primary tech stack | AWS, Azure, Google Cloud | Python, AWS, Azure |
| Industries served | Healthcare, FinTech, Retail & E-commerce, Manufacturing, Energy | FinTech, Media & Entertainment, Healthcare, Retail & E-commerce, Travel & Hospitality |
SoftServe vs DataArt: overview
SoftServe
SoftServe was founded in 1993 in Lviv, Ukraine and now operates with a US headquarters in Austin, Texas and a European headquarters in Lviv, employing more than 12,000 people across 58 offices in 14 countries (with one source citing roughly 10,336 as of a recent count). The company's offerings span digital engineering, data analytics, cloud services, AI, machine learning, and IoT, and it ranked seventh among more than 130 Western European companies in Clutch's 2019 software development category. Its scale and 30+ year history make it a large, generalist engineering firm with AI as one of several core practices.
DataArt
DataArt was founded in 1997 in New York City by Eugene Goland and has grown to more than 6,000 engineers across 40+ locations in the US, UK, Europe, Latin America, India, and the Middle East. The firm delivers data, analytics, and AI platforms for finance, media, healthcare, retail, and travel clients, built around Artisyn, its AI-enabled operating model that embeds AI agents and governance frameworks across the software development lifecycle, including regulated industries. Clients cited on its Clutch profile include Priceline, Ocado Technology, Legal & General, and Flutter Entertainment.
Services and capabilities: SoftServe vs DataArt
| Capability | SoftServe | DataArt |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✓ | ✗ |
| Generative AI | ✗ | ✓ |
| AI Consulting | ✓ | ✓ |
Tech stack comparison: SoftServe vs DataArt
| Framework / platform | SoftServe | DataArt |
|---|---|---|
| TensorFlow | ✓ | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| Kubernetes | ✓ | ✓ |
Pricing comparison: SoftServe vs DataArt
| Criterion | SoftServe | DataArt |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Managed engagement, Time & materials, Staff augmentation | Managed engagement, Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: SoftServe vs DataArt
| Dimension | SoftServe | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, FinTech, Retail & E-commerce | FinTech, Media & Entertainment, Healthcare |
| Best use cases | Large enterprise wants a single vendor covering AI/ML alongside cloud, data analytics, and IoT services., Company needs a choice between US and EU contracting jurisdictions from the same firm. | Regulated financial services or healthcare company needs AI delivery with a built-in governance framework., Enterprise wants a vendor with named, publicly referenceable clients like Priceline and Legal & General. |
| Typical project type | Managed engagement | Managed engagement |
SoftServe vs DataArt: pros and cons
| SoftServe | |
|---|---|
| + | 12,000+ employees across 58 offices in 14 countries gives it enterprise-scale delivery capacity and geographic redundancy. |
| + | 31 years of continuous operation (since 1993) through multiple technology cycles, including the post-2022 relocation pressures on Ukraine-founded firms. |
| + | Ranked 7th among 130+ Western European companies in Clutch's 2019 software development category, an independently sourced recognition. |
| + | Dual US/Ukraine headquarters structure gives clients a choice of contracting jurisdiction. |
| - | 12,000+ person scale means AI/ML is one of several mature practices (alongside cloud, data analytics, IoT) rather than the firm's core identity. |
| - | Reported employee counts vary by thousands across sources (10,336 vs. 12,000+), reflecting the difficulty of pinning down exact current headcount at this scale. |
| DataArt | |
|---|---|
| + | Named enterprise clients (Priceline, Ocado Technology, Legal & General, Flutter Entertainment) are independently verifiable via public case studies. |
| + | 27+ years of operating history (since 1997) gives it one of the longer track records in this list. |
| + | Artisyn operating model specifically addresses AI governance for regulated industries like financial services and healthcare, a genuine differentiator. |
| + | 6,000+ engineers across 40+ global locations provide substantial delivery capacity and geographic flexibility. |
| - | At 6,000+ employees, engagements are structured around managed delivery rather than close founder-level involvement. |
| - | AI/ML is one of several core service lines (alongside broader data/analytics platform work), not the firm's exclusive focus. |
Who should choose SoftServe?
SoftServe is the right choice for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices..
31 years of engineering history (since 1993) with dual US and Ukraine headquarters and 12,000+ employees.. Minimum engagement starts at Not published. Works best with clients in Healthcare, FinTech, Retail & E-commerce, Manufacturing, Energy.
Who should choose DataArt?
DataArt is the right choice for regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks..
Artisyn, a proprietary AI-enabled operating model embedding governance and AI agents across the delivery lifecycle.. Minimum engagement starts at Not published. Works best with clients in FinTech, Media & Entertainment, Healthcare, Retail & E-commerce, Travel & Hospitality.
Decision matrix: SoftServe vs DataArt
| 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 | DataArt |
| Your budget is at the lower end | Compare: SoftServe (Not published) vs DataArt (Not published) |
| You need specialist depth in a specific vertical | SoftServe |
| You need production MLOps support after model launch | SoftServe |
| You need consulting before committing to a build | SoftServe |
Use case fit: SoftServe vs DataArt
| Use case | SoftServe fit | DataArt fit | Winner |
|---|---|---|---|
| Large enterprise wants a single vendor covering AI/ML alongside cloud, data analytics, and IoT services. | Strong | Strong | Both equally |
| Company needs a choice between US and EU contracting jurisdictions from the same firm. | Strong | Strong | Both equally |
| Regulated financial services or healthcare company needs AI delivery with a built-in governance framework. | Limited | Strong | DataArt |
| Enterprise wants a vendor with named, publicly referenceable clients like Priceline and Legal & General. | Strong | Strong | Both equally |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: SoftServe vs DataArt
SoftServe (4.0/5) is the stronger overall choice for most Machine Learning Development projects. 31 years of engineering history (since 1993) with dual US and Ukraine headquarters and 12,000+ employees.. It is best for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices..
DataArt (3.9/5) is the better choice when regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks.. If your situation matches those criteria, DataArt is a competitive option.
Related comparisons
SoftServe vs DataArt FAQ
Is SoftServe better than DataArt?
SoftServe (4.0/5) scores higher overall, but "better" depends on your use case. SoftServe is better for enterprises that want an established, dual-HQ (US/Ukraine) engineering firm with AI as one of several mature practices.. DataArt is better for regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks..
How do SoftServe and DataArt differ in pricing?
SoftServe uses time & materials, managed engagement pricing with a minimum engagement of Not published. DataArt uses time & materials, managed engagement pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: SoftServe or DataArt?
SoftServe 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 SoftServe and DataArt?
SoftServe's primary differentiator is: 31 years of engineering history (since 1993) with dual us and ukraine headquarters and 12,000+ employees.. DataArt's primary differentiator is: artisyn, a proprietary ai-enabled operating model embedding governance and ai agents across the delivery lifecycle.. They also differ in team size (12,000+ vs 6,000+), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, FinTech vs FinTech, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.