AtliQ Technologies vs DataArt: full comparison for 2026
Quick verdict
AtliQ Technologies (3.9/5) edges ahead of DataArt (3.9/5) overall. AtliQ Technologies is the better choice for budget-conscious teams wanting AI added to a product build. DataArt is the stronger option for enterprises in finance or healthcare needing AI at global scale. The right choice depends on your project size, budget, and required tech stack.
AtliQ Technologies vs DataArt: head-to-head summary
| Criterion | AtliQ Technologies | DataArt |
|---|---|---|
| Founded | 2017 | 1997 |
| HQ | Vadodara, India | New York, United States |
| Team size | 50-220 | 5,700+ |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | US and India presence at startup-friendly pricing for a firm founded in 2017 | Nearly 30 years of engineering history across 30-plus global delivery locations |
| Pricing model | Fixed project or dedicated team | Dedicated team or retainer |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, scikit-learn, AWS | Python, AWS, Azure |
| Industries served | Retail & e-commerce, SaaS, Fintech | Financial services, Healthcare, Media & entertainment, Travel & hospitality |
AtliQ Technologies vs DataArt: overview
AtliQ Technologies
AtliQ Technologies was founded in 2017 by Bhavin Patel and Dhaval Patel, and is based in Vadodara, Gujarat with an additional office in New Jersey. Public employee counts vary sharply, from roughly 42 to over 220 depending on the source and reporting date, which is worth confirming directly given how young the company is relative to others on this list. The firm's core work is software product and application development, with AI-driven data analysis added as a newer service rather than a founding specialty.
DataArt
DataArt was founded in 1997 by Eugene Goland and is headquartered in New York City, with roughly 5,700 employees spread across more than 30 locations in the US, Europe, the UK, Latin America, and the UAE. The firm delivers data, analytics, and AI platforms for finance, media and entertainment, healthcare and life sciences, retail, and travel and hospitality clients. Nearly three decades of operating history gives it a longer track record than almost every other firm on this list, though AI is delivered as part of a broader software engineering practice rather than a standalone specialty.
Services and capabilities: AtliQ Technologies vs DataArt
| Capability | AtliQ Technologies | DataArt |
|---|---|---|
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| AI consulting | ✗ | ✗ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: AtliQ Technologies vs DataArt
| Framework / platform | AtliQ Technologies | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | ✓ |
Pricing comparison: AtliQ Technologies vs DataArt
| Criterion | AtliQ Technologies | DataArt |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Dedicated team | Dedicated team, Retainer |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: AtliQ Technologies vs DataArt
| Dimension | AtliQ Technologies | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & e-commerce, SaaS, Fintech | Financial services, Healthcare, Media & entertainment |
| Best use cases | Adding basic AI-driven analytics to a product already in development., Getting a budget-friendly product build where AI is a smaller part of the overall scope. | Building AI-driven analytics platforms for finance or healthcare clients with strict compliance needs., Running a long-term AI and data engineering program with a financially established vendor. |
| Typical project type | Fixed project | Dedicated team |
AtliQ Technologies vs DataArt: pros and cons
| AtliQ Technologies | |
|---|---|
| + | Combined India and New Jersey presence gives clients a US point of contact at India-based delivery cost. |
| + | Founder-led team stays close to project delivery at this size. |
| + | AI added on top of an existing product development practice, not offered in isolation. |
| + | Younger firm tends to price more competitively than established mid-market vendors. |
| - | Public employee figures vary by nearly 5x, making true team capacity hard to confirm |
| - | Shorter operating history than most other firms on this list |
| DataArt | |
|---|---|
| + | Nearly three decades of software engineering history, among the longest on this list. |
| + | 5,700-plus employees across 30-plus locations globally. |
| + | Named industry focus areas (finance, healthcare, travel) show real vertical depth. |
| + | Data and analytics platform experience supports AI work that needs solid data foundations. |
| - | AI sits inside a much broader software engineering practice rather than being the firm's core identity |
| - | Enterprise scale typically means slower onboarding than smaller, more agile AI boutiques |
Who should choose AtliQ Technologies?
A typical fit: adding basic AI-driven analytics to a product already in development.
US and India presence at startup-friendly pricing for a firm founded in 2017. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, SaaS, Fintech.
Who should choose DataArt?
A typical fit: building AI-driven analytics platforms for finance or healthcare clients with strict compliance needs.
Nearly 30 years of engineering history across 30-plus global delivery locations. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Media & entertainment, Travel & hospitality.
Decision matrix: AtliQ Technologies vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | AtliQ Technologies |
| You need a large dedicated team for an ongoing programme | AtliQ Technologies |
| Your budget is at the lower end | Compare: AtliQ Technologies (Not disclosed) vs DataArt (Not disclosed) |
| You need specialist depth in a specific vertical | DataArt |
| 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: AtliQ Technologies vs DataArt
| Use case | AtliQ Technologies fit | DataArt fit | Winner |
|---|---|---|---|
| Adding basic AI-driven analytics to a product already in development. | Strong | Limited | AtliQ Technologies |
| Getting a budget-friendly product build where AI is a smaller part of the overall scope. | Strong | Limited | AtliQ Technologies |
| Building AI-driven analytics platforms for finance or healthcare clients with strict compliance needs. | Limited | Strong | DataArt |
| Running a long-term AI and data engineering program with a financially established vendor. | Limited | Strong | DataArt |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: AtliQ Technologies vs DataArt
AtliQ Technologies (3.9/5) is the stronger overall choice for most AI Development projects. US and India presence at startup-friendly pricing for a firm founded in 2017.
DataArt (3.9/5) is worth a look if you need running a long-term AI and data engineering program with a financially established vendor. If your situation matches that, DataArt is a competitive option.
Related comparisons
AtliQ Technologies vs DataArt FAQ
Is AtliQ Technologies better than DataArt?
AtliQ Technologies (3.9/5) scores higher overall, but "better" depends on your use case. AtliQ Technologies's strongest advantage: combined India and New Jersey presence gives clients a US point of contact at India-based delivery cost. DataArt's strongest advantage: nearly three decades of software engineering history, among the longest on this list.
How do AtliQ Technologies and DataArt differ in pricing?
AtliQ Technologies uses fixed project or dedicated team pricing. DataArt uses dedicated team or retainer pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: AtliQ Technologies or DataArt?
AtliQ Technologies 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 AtliQ Technologies and DataArt?
AtliQ Technologies's primary differentiator is: US and India presence at startup-friendly pricing for a firm founded in 2017. DataArt's primary differentiator is: nearly 30 years of engineering history across 30-plus global delivery locations. They also differ in team size (50-220 vs 5,700+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Retail & e-commerce, SaaS vs Financial services, Healthcare).
Verify all details directly with each company before making a decision.