Quantiphi vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
Quantiphi (4.4/5) edges ahead of DataArt (3.9/5) overall. Quantiphi is the better choice for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering.. DataArt is the stronger option for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs DataArt: head-to-head summary
| Criterion | Quantiphi | DataArt |
|---|---|---|
| Founded | 2013 | 1997 |
| HQ | Marlborough, Massachusetts, USA | New York, USA |
| Team size | 1,001–5,000 | 5,001–10,000 |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Best for | Enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering. | Enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner. |
| Pricing model | Fixed project and managed AI services | Fixed project, dedicated team, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, Google Cloud Vertex AI | Python, Azure OpenAI, AWS |
| Industries served | Financial Services, Healthcare, Media, Technology/SaaS | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality |
Quantiphi vs DataArt: overview
Quantiphi
Quantiphi is an AI-first digital engineering company founded in 2013 by Vivek Khemani, Asif Hasan, Ritesh Patel, and Reghu Hariharan, headquartered in Marlborough, Massachusetts. Reported headcount is roughly 2,670–3,927 employees depending on source, making it one of the larger, more established AI-native firms on this list, with strong focus on financial services and cloud-native ML platform engineering.
DataArt
DataArt is a software engineering and consulting company founded in 1997 in New York by Eugene Goland, with roughly 5,400 employees across more than 30 locations spanning the US, Europe, Latin America, India, and the UAE. The firm added an Advanced AI Strategy Consulting service line in 2024, delivering data, analytics, and AI/ML work alongside its long-standing core software engineering practice.
Services and capabilities: Quantiphi vs DataArt
| Capability | Quantiphi | DataArt |
|---|---|---|
| Custom ML model development | ✓ | ✓ |
| Deep learning & computer vision | ✗ | ✗ |
| NLP & LLM / Generative AI | ✗ | ✗ |
| MLOps & production deployment | ✓ | ✗ |
| Data engineering | ✓ | ✓ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✓ |
Tech stack comparison: Quantiphi vs DataArt
| Framework / platform | Quantiphi | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| Databricks | N/A | ✓ |
| LangChain | N/A | N/A |
Pricing comparison: Quantiphi vs DataArt
| Criterion | Quantiphi | DataArt |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Fixed project, Managed services | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / not published | Enterprise / not published |
Target audience comparison: Quantiphi vs DataArt
| Dimension | Quantiphi | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Financial Services, Healthcare, Media | Financial Services, Media & Entertainment, Healthcare |
| Best use cases | Enterprise financial-services AI programs requiring both scale and deep ML expertise, Cloud-native ML platform builds on GCP, AWS, or Azure at production scale | Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery, Media or travel companies needing broad-based data and AI/ML capability |
| Typical project type | Fixed project | Fixed project |
Quantiphi vs DataArt: pros and cons
| Quantiphi | |
|---|---|
| + | Founded as an AI-first company rather than a generalist IT firm that later added an AI practice |
| + | Enterprise-scale headcount (2,600+) supports large, multi-region programs |
| + | Strong cloud-native ML platform engineering, reducing gaps between model development and production deployment |
| + | 13 years of continuous focus on applied AI and analytics |
| - | Scale and enterprise sales process may be slower and less accessible for small pilot projects than boutique competitors |
| - | Recent employee counts show a reported year-over-year headcount decline (~4% per one source), worth asking about directly |
| - | Minimum engagement size and standard pricing are not publicly disclosed |
| DataArt | |
|---|---|
| + | 28 years of continuous operation under the same founder-led leadership |
| + | 30+ global delivery locations across five regions supports broad geographic coverage |
| + | Named AI Strategy Consulting service line launched in 2024 shows deliberate recent AI investment |
| + | Broad industry coverage spanning finance, media, healthcare, and travel |
| - | AI Strategy Consulting is a comparatively recent addition (2024) versus firms with a decade-plus dedicated AI/ML focus |
| - | 5,400-employee scale sits within a broad general software-engineering practice rather than an AI-first firm |
| - | Minimum engagement size not publicly disclosed |
Who should choose Quantiphi?
Quantiphi is the right choice for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering..
AI-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist IT outsourcing.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Healthcare, Media, Technology/SaaS.
Who should choose DataArt?
DataArt is the right choice for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality.
Decision matrix: Quantiphi vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Quantiphi |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Compare: Quantiphi (Not published) vs DataArt (Not published) |
| You need specialist depth in a specific vertical | DataArt |
| You need staff augmentation or team extension | DataArt |
| You need consulting before committing to a build | Quantiphi |
Use case fit: Quantiphi vs DataArt
| Use case | Quantiphi fit | DataArt fit | Winner |
|---|---|---|---|
| Enterprise financial-services AI programs requiring both scale and deep ML expertise | Strong | Strong | Both equally |
| Cloud-native ML platform builds on GCP, AWS, or Azure at production scale | Strong | Limited | Quantiphi |
| Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery | Limited | Strong | DataArt |
| Media or travel companies needing broad-based data and AI/ML capability | Limited | Strong | DataArt |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Quantiphi vs DataArt
Quantiphi (4.4/5) is the stronger overall choice for most Machine Learning Development projects. AI-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist IT outsourcing.. It is best for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering..
DataArt (3.9/5) is the better choice when enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. If your situation matches those criteria, DataArt is a competitive option.
Related comparisons
Quantiphi vs DataArt FAQ
Is Quantiphi better than DataArt?
Quantiphi (4.4/5) scores higher overall, but "better" depends on your use case. Quantiphi is better for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering.. DataArt is better for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
How do Quantiphi and DataArt differ in pricing?
Quantiphi uses fixed project and managed ai services pricing with a minimum engagement of Not published. DataArt uses fixed project, dedicated team, staff augmentation 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: Quantiphi 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 agency before shortlisting.
What are the main differences between Quantiphi and DataArt?
Quantiphi's primary differentiator is: ai-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist it outsourcing.. DataArt's primary differentiator is: 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated ai strategy consulting service line.. They also differ in team size (1,001–5,000 vs 5,001–10,000), minimum engagement (Not published vs Not published), and primary industries served (Financial Services, Healthcare vs Financial Services, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.