Yalantis vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
Yalantis (4.0/5) edges ahead of DataArt (3.9/5) overall. Yalantis is the better choice for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. 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.
Yalantis vs DataArt: head-to-head summary
| Criterion | Yalantis | DataArt |
|---|---|---|
| Founded | 2008 | 1997 |
| HQ | Larnaca, Cyprus | New York, New York, United States |
| Team size | 500+ | 6,000+ |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Best for | Compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms. | Regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks. |
| Pricing model | Fixed project, dedicated team | Time & materials, managed engagement |
| Min. engagement | $10,000 | Not published |
| Primary tech stack | AWS SageMaker, Azure ML, Google Cloud Vertex AI | Python, AWS, Azure |
| Industries served | Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain | FinTech, Media & Entertainment, Healthcare, Retail & E-commerce, Travel & Hospitality |
Yalantis vs DataArt: overview
Yalantis
Yalantis was founded in 2008 with headquarters in Larnaca, Cyprus and development hubs in Dnipro, Kyiv, and Lviv, Ukraine, growing to roughly 500 specialists. The firm positions itself as a 'compliance-first engineering partner,' building high-performance ML models across Amazon, Microsoft Azure, and Google Cloud ML platforms, including data preparation, model selection, training, deployment, and multimodal LLM processing for visual and text data. Project costs are reported to range from $10,000 to over $800,000, indicating the firm handles both small scoped projects and large enterprise programs.
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: Yalantis vs DataArt
| Capability | Yalantis | DataArt |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✓ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✓ |
Tech stack comparison: Yalantis vs DataArt
| Framework / platform | Yalantis | DataArt |
|---|---|---|
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: Yalantis vs DataArt
| Criterion | Yalantis | DataArt |
|---|---|---|
| Minimum engagement | $10,000 | Not published |
| Engagement models | Fixed project, Dedicated team, Staff augmentation | Managed engagement, Time & materials, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Yalantis vs DataArt
| Dimension | Yalantis | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, IoT & Embedded Systems, FinTech | FinTech, Media & Entertainment, Healthcare |
| Best use cases | Healthcare or IoT company needs ML development from a compliance-first engineering partner., Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. | 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 | Fixed project | Managed engagement |
Yalantis vs DataArt: pros and cons
| Yalantis | |
|---|---|
| + | Compliance-first positioning is a genuine differentiator for regulated industries like healthcare and embedded/IoT systems. |
| + | Multi-cloud ML delivery capability (AWS, Azure, GCP) avoids vendor lock-in to a single hyperscaler. |
| + | Wide project-cost range ($10,000–$800,000+) means the firm can serve both small scoped projects and large programs without switching vendors. |
| + | 500+ specialists across three Ukrainian development hubs provides meaningful delivery redundancy. |
| - | IoT and hardware engineering heritage means ML is one of several engineering disciplines rather than the firm's sole focus. |
| - | Larnaca, Cyprus legal HQ with all technical delivery in Ukraine is standard for the region but worth confirming for contract jurisdiction purposes. |
| 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 Yalantis?
Yalantis is the right choice for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..
Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof.. Minimum engagement starts at $10,000. Works best with clients in Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain.
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: Yalantis vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Yalantis |
| You need a large dedicated team for an ongoing programme | Yalantis |
| Your budget is at the lower end | Compare: Yalantis ($10,000) vs DataArt (Not published) |
| You need specialist depth in a specific vertical | DataArt |
| You need production MLOps support after model launch | Yalantis |
| You need consulting before committing to a build | DataArt |
Use case fit: Yalantis vs DataArt
| Use case | Yalantis fit | DataArt fit | Winner |
|---|---|---|---|
| Healthcare or IoT company needs ML development from a compliance-first engineering partner. | Strong | Strong | Both equally |
| Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. | 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. | Limited | Strong | DataArt |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: Yalantis vs DataArt
Yalantis (4.0/5) is the stronger overall choice for most Machine Learning Development projects. Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof.. It is best for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..
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
Yalantis vs DataArt FAQ
Is Yalantis better than DataArt?
Yalantis (4.0/5) scores higher overall, but "better" depends on your use case. Yalantis is better for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. DataArt is better for regulated-industry enterprises (finance, healthcare) that need AI delivery with built-in governance frameworks..
How do Yalantis and DataArt differ in pricing?
Yalantis uses fixed project, dedicated team pricing with a minimum engagement of $10,000. 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: Yalantis or DataArt?
DataArt 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 Yalantis and DataArt?
Yalantis's primary differentiator is: compliance-first positioning combined with multi-cloud ml delivery (aws, azure, gcp) under one roof.. 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 (500+ vs 6,000+), minimum engagement ($10,000 vs Not published), and primary industries served (Healthcare, IoT & Embedded Systems vs FinTech, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.