Provectus vs MobiDev: full comparison for 2026
Last updated: July 2026
Quick verdict
Provectus (4.5/5) edges ahead of MobiDev (4.3/5) overall. Provectus is the better choice for mid-market companies that need cloud data infrastructure and ML model development handled by the same integrator.. MobiDev is the stronger option for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. The right choice depends on your project size, budget, and required tech stack.
Provectus vs MobiDev: head-to-head summary
| Criterion | Provectus | MobiDev |
|---|---|---|
| Founded | 2010 | 2009 |
| HQ | Palo Alto, USA | Norcross, USA (delivery centers: Lodz, Poland and Chernivtsi, Ukraine) |
| Team size | 501–1,000 | 201–500 |
| Rating | 4.5 / 5 | 4.3 / 5 |
| Best for | Mid-market companies that need cloud data infrastructure and ML model development handled by the same integrator. | Small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner. |
| Pricing model | Not published; project and dedicated team | Time & Material, Fixed project |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, AWS, GCP | Python, Computer vision frameworks, Cloud ML platforms |
| Industries served | Cross-industry mid-market, Healthcare, Retail, Media | Healthcare, Retail, Manufacturing, Media |
Provectus vs MobiDev: overview
Provectus
Provectus is an AI-first systems integrator and solutions provider founded in 2010 and headquartered in Palo Alto, California, with an international delivery team of more than 600 people spread across Ukraine, the US, Canada, and several other countries. The company's practice spans cloud engineering, big data engineering, and applied AI/ML, reflecting its origin as a broader cloud and data engineering consultancy that layered in machine learning capability. It positions itself specifically toward the mid-market rather than either small startups or the largest global enterprises. Founder and CEO Stepan Pushkarev continues to lead the company.
MobiDev
MobiDev is a software development and consulting company founded in 2009, with business units in Norcross, Georgia (US) and Sheffield (UK), and R&D delivery centers in Lodz, Poland and Chernivtsi, Ukraine staffed by more than 400 engineers. Its consulting services span data science, machine learning, augmented reality, IoT, and DevOps, aimed at small and medium-sized companies rather than large enterprises. The company reports a 100 percent project success rate on Upwork and was named the #1 machine learning development company by Clutch in 2021.
Services and capabilities: Provectus vs MobiDev
| Capability | Provectus | MobiDev |
|---|---|---|
| Custom model training | ✓ | ✓ |
| Fine-tuning & adaptation | ✗ | ✗ |
| MLOps pipeline | ✓ | ✗ |
| Model deployment & serving | ✓ | ✗ |
| Data engineering for ML | ✓ | ✓ |
| ML infrastructure management | ✓ | ✗ |
| Computer vision | ✗ | ✓ |
| NLP & LLM development | ✗ | ✗ |
| Forecasting & time-series modeling | ✗ | ✗ |
| ML strategy consulting | ✗ | ✓ |
Tech stack comparison: Provectus vs MobiDev
| Framework / platform | Provectus | MobiDev |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Amazon Bedrock | N/A | N/A |
| Google Cloud | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Kubernetes | ✓ | ✓ |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: Provectus vs MobiDev
| Criterion | Provectus | MobiDev |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team, Cloud/data engineering retainer | Time & Material, Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Provectus vs MobiDev
| Dimension | Provectus | MobiDev |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Cross-industry mid-market, Healthcare, Retail | Healthcare, Retail, Manufacturing |
| Best use cases | Building the data pipeline and feature store underneath a new ML model program, Migrating legacy big-data infrastructure to a cloud-native stack in preparation for ML workloads | Building a custom ML model for a small or medium-sized business without an internal data science team, Combining computer vision or ML work with broader mobile/IoT product development |
| Typical project type | Project-based | Time & Material |
Provectus vs MobiDev: pros and cons
| Provectus | |
|---|---|
| + | Fifteen-year operating history with a clear mid-market positioning. |
| + | Strong big-data/cloud engineering foundation underpins its ML delivery, useful when data infrastructure is the bottleneck. |
| + | 600+ person distributed team offers meaningful delivery capacity without full enterprise-scale overhead. |
| + | Explicit mid-market focus avoids the "too small" or "too generic-enterprise" mismatch some buyers hit elsewhere. |
| - | Team-size reporting varies by source (500–1,000+), indicating some uncertainty in exact headcount. |
| - | Named, public case studies with concrete client outcomes are limited in available search results. |
| - | Pricing model and minimums are not published. |
| - | Positioning as a broad AI/cloud integrator means ML model development competes for attention with other service lines. |
| MobiDev | |
|---|---|
| + | Historical Clutch #1 ranking in machine learning development (2021). |
| + | 16 Clutch reviews with consistently positive delivery feedback. |
| + | Explicit focus on small/medium-sized clients, a niche underserved by larger enterprise-first firms. |
| + | Multi-country delivery footprint (Poland, Ukraine) with 400+ engineers provides meaningful bench depth. |
| - | Team-size figures vary by source (roughly 200–500), indicating some reporting inconsistency. |
| - | SME focus may mean less experience with very large, complex enterprise-scale ML platforms. |
| - | Machine learning is one of several practice areas (alongside AR, IoT) rather than the sole focus. |
| - | Minimum engagement size is not published, requiring a scoping conversation. |
Who should choose Provectus?
Provectus is the right choice for mid-market companies that need cloud data infrastructure and ML model development handled by the same integrator..
Grew out of cloud and big-data engineering roots, giving it particular strength in the data infrastructure layer underneath ML models, not just the models themselves.. Minimum engagement starts at Not published. Works best with clients in Cross-industry mid-market, Healthcare, Retail, Media.
Who should choose MobiDev?
MobiDev is the right choice for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..
Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Retail, Manufacturing, Media.
Decision matrix: Provectus vs MobiDev
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | MobiDev |
| You need a large dedicated team for an ongoing programme | Provectus |
| Your budget is at the lower end | Compare: Provectus (Not published) vs MobiDev (Not published) |
| You need specialist depth in a specific vertical | Provectus |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | MobiDev |
Use case fit: Provectus vs MobiDev
| Use case | Provectus fit | MobiDev fit | Winner |
|---|---|---|---|
| Building the data pipeline and feature store underneath a new ML model program | Strong | Strong | Both equally |
| Migrating legacy big-data infrastructure to a cloud-native stack in preparation for ML workloads | Strong | Limited | Provectus |
| Building a custom ML model for a small or medium-sized business without an internal data science team | Strong | Strong | Both equally |
| Combining computer vision or ML work with broader mobile/IoT product development | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Limited | Provectus |
Verdict: Provectus vs MobiDev
Provectus (4.5/5) is the stronger overall choice for most ML Model Development projects. Grew out of cloud and big-data engineering roots, giving it particular strength in the data infrastructure layer underneath ML models, not just the models themselves.. It is best for mid-market companies that need cloud data infrastructure and ML model development handled by the same integrator..
MobiDev (4.3/5) is the better choice when small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. If your situation matches those criteria, MobiDev is a competitive option.
Related comparisons
Provectus vs MobiDev FAQ
Is Provectus better than MobiDev?
Provectus (4.5/5) scores higher overall, but "better" depends on your use case. Provectus is better for mid-market companies that need cloud data infrastructure and ML model development handled by the same integrator.. MobiDev is better for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..
How do Provectus and MobiDev differ in pricing?
Provectus uses not published; project and dedicated team pricing with a minimum engagement of Not published. MobiDev uses time & material, fixed project 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: Provectus or MobiDev?
Provectus 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 Provectus and MobiDev?
Provectus's primary differentiator is: grew out of cloud and big-data engineering roots, giving it particular strength in the data infrastructure layer underneath ml models, not just the models themselves.. MobiDev's primary differentiator is: historical clutch #1 ranking for machine learning development (2021) combined with a specifically sme-oriented service model.. They also differ in team size (501–1,000 vs 201–500), minimum engagement (Not published vs Not published), and primary industries served (Cross-industry mid-market, Healthcare vs Healthcare, Retail).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.