Fractal Analytics vs MobiDev: full comparison for 2026
Last updated: July 2026
Quick verdict
Fractal Analytics (4.4/5) edges ahead of MobiDev (4.2/5) overall. Fractal Analytics is the better choice for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record.. MobiDev is the stronger option for retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record.. The right choice depends on your project size, budget, and required tech stack.
Fractal Analytics vs MobiDev: head-to-head summary
| Criterion | Fractal Analytics | MobiDev |
|---|---|---|
| Founded | 2000 | 2009 |
| HQ | Mumbai, India / New York, USA | Atlanta, Georgia, USA |
| Team size | 5,001–10,000 | 201–500 |
| Rating | 4.4 / 5 | 4.2 / 5 |
| Best for | Large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record. | Retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record. |
| Pricing model | Fixed project and managed analytics engagements | Fixed project and dedicated team |
| Min. engagement | Not published | $20K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, OpenCV |
| Industries served | Retail, Financial Services, Healthcare, Technology/SaaS | Retail, Hospitality, Health & Fitness, Sports |
Fractal Analytics vs MobiDev: overview
Fractal Analytics
Fractal Analytics is a multinational AI and data analytics company founded in 2000 in Mumbai by Srikanth Velamakanni, Pranay Agrawal, Nirmal Palaparthi, Pradeep Suryanarayan, and Ramakrishna Reddy, with dual headquarters in Mumbai and New York. The company completed an initial public offering on India's National Stock Exchange and Bombay Stock Exchange in February 2026, becoming the first Indian AI company to go public, and reports roughly 5,000–6,900 employees across 18 global locations.
MobiDev
MobiDev is a custom software development company founded in 2009, headquartered in Atlanta, Georgia, with R&D centers in Lodz, Poland and Chernivtsi, Ukraine, and roughly 290–400 engineers. CEO Oleg Lola initiated a dedicated AI/ML practice in 2018, and the company has since delivered more than 65 AI/ML products, concentrated in retail, hospitality, fitness, sports, and health/wellness.
Services and capabilities: Fractal Analytics vs MobiDev
| Capability | Fractal Analytics | MobiDev |
|---|---|---|
| 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: Fractal Analytics vs MobiDev
| Framework / platform | Fractal Analytics | MobiDev |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
| LangChain | N/A | N/A |
Pricing comparison: Fractal Analytics vs MobiDev
| Criterion | Fractal Analytics | MobiDev |
|---|---|---|
| Minimum engagement | Not published | $20K |
| Engagement models | Fixed project, Managed services | Fixed project, Dedicated team |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Enterprise / not published | Accessible |
Target audience comparison: Fractal Analytics vs MobiDev
| Dimension | Fractal Analytics | MobiDev |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Retail, Financial Services, Healthcare | Retail, Hospitality, Health & Fitness |
| Best use cases | Enterprise AI and analytics transformation programs at global scale, Buyers who specifically want a publicly-listed AI vendor for procurement/compliance reasons | Retail or hospitality companies wanting computer-vision or recommendation features built into an existing product, Health and fitness apps needing an ML-driven personalization or tracking feature |
| Typical project type | Fixed project | Fixed project |
Fractal Analytics vs MobiDev: pros and cons
| Fractal Analytics | |
|---|---|
| + | 25 years of continuous operation, among the longest track records on this list |
| + | Public listing (NSE/BSE, Feb 2026) adds a level of financial disclosure most private competitors lack |
| + | 5,000+ employees across 18 countries supports very large, globally distributed programs |
| + | Founding team has remained core to the company since 2000 |
| - | Enterprise scale and public-company overhead can mean longer sales cycles than boutique competitors |
| - | Broad analytics positioning means ML-specialist depth is one part of a wider data/AI portfolio |
| - | Minimum engagement size not publicly disclosed |
| MobiDev | |
|---|---|
| + | 65+ delivered AI/ML products gives a concrete, countable delivery track record rather than general marketing claims |
| + | Deliberate AI/ML practice build-out since 2018, rather than a very recent pivot |
| + | Named vertical concentration (retail, hospitality, fitness, health) supports domain-specific product experience |
| + | Mid-size team (290–400) balances specialist focus with real delivery capacity |
| - | Narrower industry focus than horizontal AI consultancies serving finance, healthcare, and manufacturing broadly |
| - | Smaller scale than the large enterprise IT firms on this list, limiting very large multi-team programs |
| - | AI/ML sits alongside a broader general custom-software-development practice |
Who should choose Fractal Analytics?
Fractal Analytics is the right choice for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record..
First Indian AI company to complete an IPO (NSE/BSE, February 2026), adding public financial transparency.. Minimum engagement starts at Not published. Works best with clients in Retail, Financial Services, Healthcare, Technology/SaaS.
Who should choose MobiDev?
MobiDev is the right choice for retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record..
65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals.. Minimum engagement starts at $20K. Works best with clients in Retail, Hospitality, Health & Fitness, Sports.
Decision matrix: Fractal Analytics vs MobiDev
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Fractal Analytics |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | Compare: Fractal Analytics (Not published) vs MobiDev ($20K) |
| You need specialist depth in a specific vertical | Fractal Analytics |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Fractal Analytics |
Use case fit: Fractal Analytics vs MobiDev
| Use case | Fractal Analytics fit | MobiDev fit | Winner |
|---|---|---|---|
| Enterprise AI and analytics transformation programs at global scale | Strong | Limited | Fractal Analytics |
| Buyers who specifically want a publicly-listed AI vendor for procurement/compliance reasons | Strong | Limited | Fractal Analytics |
| Retail or hospitality companies wanting computer-vision or recommendation features built into an existing product | Strong | Strong | Both equally |
| Health and fitness apps needing an ML-driven personalization or tracking feature | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Fractal Analytics vs MobiDev
Fractal Analytics (4.4/5) is the stronger overall choice for most Machine Learning Development projects. First Indian AI company to complete an IPO (NSE/BSE, February 2026), adding public financial transparency.. It is best for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record..
MobiDev (4.2/5) is the better choice when retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record.. If your situation matches those criteria, MobiDev is a competitive option.
Related comparisons
Fractal Analytics vs MobiDev FAQ
Is Fractal Analytics better than MobiDev?
Fractal Analytics (4.4/5) scores higher overall, but "better" depends on your use case. Fractal Analytics is better for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record.. MobiDev is better for retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record..
How do Fractal Analytics and MobiDev differ in pricing?
Fractal Analytics uses fixed project and managed analytics engagements pricing with a minimum engagement of Not published. MobiDev uses fixed project and dedicated team pricing with a minimum engagement of $20K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Fractal Analytics or MobiDev?
Fractal Analytics 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 Fractal Analytics and MobiDev?
Fractal Analytics's primary differentiator is: first indian ai company to complete an ipo (nse/bse, february 2026), adding public financial transparency.. MobiDev's primary differentiator is: 65+ delivered ai/ml products concentrated in retail, hospitality, fitness, and health/wellness verticals.. They also differ in team size (5,001–10,000 vs 201–500), minimum engagement (Not published vs $20K), and primary industries served (Retail, Financial Services vs Retail, Hospitality).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.