LatentView Analytics vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
LatentView Analytics (3.9/5) edges ahead of DataArt (3.9/5) overall. LatentView Analytics is the better choice for companies wanting analytics and BI delivery with ML capability layered in, rather than a pure-play ML specialist.. 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.
LatentView Analytics vs DataArt: head-to-head summary
| Criterion | LatentView Analytics | DataArt |
|---|---|---|
| Founded | 2006 | 1997 |
| HQ | Chennai, India | New York, USA |
| Team size | 1,001–5,000 | 5,001–10,000 |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Best for | Companies wanting analytics and BI delivery with ML capability layered in, rather than a pure-play ML specialist. | 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 analytics services | Fixed project, dedicated team, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Tableau, AWS | Python, Azure OpenAI, AWS |
| Industries served | Retail, Financial Services, Technology/SaaS, CPG | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality |
LatentView Analytics vs DataArt: overview
LatentView Analytics
LatentView Analytics is a business analytics and digital transformation consultancy founded in 2006 by Venkat Viswanathan and Pramod Jandhyala, headquartered in Chennai, India. The company completed an IPO on the NSE and BSE in December 2021, reporting record oversubscription, and now employs roughly 1,170 people. Its work spans broader business analytics and BI in addition to custom ML model development.
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: LatentView Analytics vs DataArt
| Capability | LatentView Analytics | 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: LatentView Analytics vs DataArt
| Framework / platform | LatentView Analytics | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | N/A | ✓ |
| LangChain | N/A | N/A |
Pricing comparison: LatentView Analytics vs DataArt
| Criterion | LatentView Analytics | 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: LatentView Analytics vs DataArt
| Dimension | LatentView Analytics | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Retail, Financial Services, Technology/SaaS | Financial Services, Media & Entertainment, Healthcare |
| Best use cases | Companies wanting a combined BI dashboard and predictive-model deliverable, Retail or CPG analytics programs where ML is one part of a broader reporting stack | 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 |
LatentView Analytics vs DataArt: pros and cons
| LatentView Analytics | |
|---|---|
| + | Public listing since December 2021 provides financial transparency uncommon among private competitors |
| + | 19 years of continuous operation with founders still central to the business |
| + | 1,170+ employees supports mid-to-large scale engagements |
| + | Broad BI and analytics capability useful for buyers who need reporting alongside ML |
| - | Core positioning is business analytics/BI first, with custom ML development as one offering rather than the central focus |
| - | Less specialist ML certification or AI-first branding than firms like Quantiphi or Neurons Lab |
| - | Minimum engagement size 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 LatentView Analytics?
LatentView Analytics is the right choice for companies wanting analytics and BI delivery with ML capability layered in, rather than a pure-play ML specialist..
Publicly listed (NSE/BSE since 2021) analytics firm with two decades of operating history.. Minimum engagement starts at Not published. Works best with clients in Retail, Financial Services, Technology/SaaS, CPG.
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: LatentView Analytics vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | LatentView Analytics |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Compare: LatentView Analytics (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 | DataArt |
Use case fit: LatentView Analytics vs DataArt
| Use case | LatentView Analytics fit | DataArt fit | Winner |
|---|---|---|---|
| Companies wanting a combined BI dashboard and predictive-model deliverable | Strong | Strong | Both equally |
| Retail or CPG analytics programs where ML is one part of a broader reporting stack | Strong | Limited | LatentView Analytics |
| 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: LatentView Analytics vs DataArt
LatentView Analytics (3.9/5) is the stronger overall choice for most Machine Learning Development projects. Publicly listed (NSE/BSE since 2021) analytics firm with two decades of operating history.. It is best for companies wanting analytics and BI delivery with ML capability layered in, rather than a pure-play ML specialist..
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
LatentView Analytics vs DataArt FAQ
Is LatentView Analytics better than DataArt?
LatentView Analytics (3.9/5) scores higher overall, but "better" depends on your use case. LatentView Analytics is better for companies wanting analytics and BI delivery with ML capability layered in, rather than a pure-play ML specialist.. 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 LatentView Analytics and DataArt differ in pricing?
LatentView Analytics uses fixed project and managed analytics 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: LatentView Analytics 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 LatentView Analytics and DataArt?
LatentView Analytics's primary differentiator is: publicly listed (nse/bse since 2021) analytics firm with two decades of operating history.. 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 (Retail, Financial Services vs Financial Services, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.