Sigmoid vs MobiDev: full comparison for 2026
Quick verdict
Sigmoid (4.2/5) edges ahead of MobiDev (4.2/5) overall. Sigmoid is the better choice for large enterprises, data-engineering-first ML delivery. MobiDev is the stronger option for Retail, hospitality, fitness companies — proven mid-size AI delivery. The right choice depends on your project size, budget, and required tech stack.
Sigmoid vs MobiDev: head-to-head summary
| Criterion | Sigmoid | MobiDev |
|---|---|---|
| Founded | 2013 | 2009 |
| HQ | Bengaluru, India / New York, USA | Atlanta, Georgia, USA |
| Team size | 501–1,000 | 201–500 |
| Rating | 4.2 / 5 | 4.2 / 5 |
| Primary differentiator | Data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages | 65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals |
| Pricing model | Managed services and fixed project | Fixed project and dedicated team |
| Min. engagement | Not published | $20K |
| Primary tech stack | Python, Apache Spark, Databricks | Python, TensorFlow, OpenCV |
| Industries served | Retail, Technology/SaaS, Financial Services, Media | Retail, Hospitality, Health & Fitness, Sports |
Sigmoid vs MobiDev: overview
Sigmoid
Sigmoid is a data engineering and AI consulting firm founded in 2013 by Rahul Singh, Lokesh Anand, and Mayur Rustagi. Sources differ on its primary headquarters, with some citing Bengaluru, India and others New York; reported headcount ranges from roughly 600 to 760 employees. The firm markets itself around round-the-clock data engineering and AI services for more than 25 Fortune 500 clients.
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: Sigmoid vs MobiDev
| Capability | Sigmoid | 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: Sigmoid vs MobiDev
| Framework / platform | Sigmoid | MobiDev |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | ✓ |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | ✓ | N/A |
| LangChain | N/A | N/A |
Pricing comparison: Sigmoid vs MobiDev
| Criterion | Sigmoid | MobiDev |
|---|---|---|
| Minimum engagement | Not published | $20K |
| Engagement models | Managed services, Fixed project | Fixed project, Dedicated team |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Enterprise / not published | Accessible |
Target audience comparison: Sigmoid vs MobiDev
| Dimension | Sigmoid | MobiDev |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Retail, Technology/SaaS, Financial Services | Retail, Hospitality, Health & Fitness |
| Best use cases | Building the data pipeline and the ML model together for a large enterprise client, Fortune 500 programs needing 24/7 delivery across time zones | 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 | Managed services | Fixed project |
Sigmoid vs MobiDev: pros and cons
| Sigmoid | |
|---|---|
| + | Round-the-clock delivery model across geographies and time zones supports faster iteration |
| + | 25+ named Fortune 500 clients suggests real enterprise-scale delivery credibility |
| + | Combines data engineering and AI/ML under one roof, reducing hand-off friction |
| + | 12 years of focused operation in data engineering and analytics |
| - | Public sources disagree on primary headquarters location (Bengaluru vs. New York) — confirm the contracting entity directly |
| - | Data-engineering-first positioning may mean less emphasis on cutting-edge model research than AI-first boutiques |
| - | 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 Sigmoid?
A typical fit: building the data pipeline and the ML model together for a large enterprise client.
Data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages. Minimum engagement starts at Not published. Works best with clients in Retail, Technology/SaaS, Financial Services, Media.
Who should choose MobiDev?
A typical fit: retail or hospitality companies wanting computer-vision or recommendation features built into an existing product.
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: Sigmoid vs MobiDev
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Sigmoid |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | Compare: Sigmoid (Not published) vs MobiDev ($20K) |
| You need specialist depth in a specific vertical | Sigmoid |
| 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: Sigmoid vs MobiDev
| Use case | Sigmoid fit | MobiDev fit | Winner |
|---|---|---|---|
| Building the data pipeline and the ML model together for a large enterprise client | Strong | Limited | Sigmoid |
| Fortune 500 programs needing 24/7 delivery across time zones | Strong | Limited | Sigmoid |
| 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 | Limited | Strong | MobiDev |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Sigmoid vs MobiDev
Sigmoid (4.2/5) is the stronger overall choice for most Machine Learning Development projects. Data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages.
MobiDev (4.2/5) is worth a look if you need health and fitness apps needing an ML-driven personalization or tracking feature. If your situation matches that, MobiDev is a competitive option.
Related comparisons
Sigmoid vs MobiDev FAQ
Is Sigmoid better than MobiDev?
Sigmoid (4.2/5) scores higher overall, but "better" depends on your use case. Sigmoid's strongest advantage: round-the-clock delivery model across geographies and time zones supports faster iteration. MobiDev's strongest advantage: 65+ delivered AI/ML products gives a concrete, countable delivery track record rather than general marketing claims.
How do Sigmoid and MobiDev differ in pricing?
Sigmoid uses managed services and fixed project 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: Sigmoid or MobiDev?
Sigmoid 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 Sigmoid and MobiDev?
Sigmoid's primary differentiator is: data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages. 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 (501–1,000 vs 201–500), minimum engagement (Not published vs $20K), and primary industries served (Retail, Technology/SaaS vs Retail, Hospitality).