Best ML Model Development Companies

MobiDev vs Infosys: full comparison for 2026

Last updated: July 2026

Quick verdict

MobiDev (4.3/5) edges ahead of Infosys (3.9/5) overall. MobiDev is the better choice for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. Infosys is the stronger option for very large global enterprises wanting a substantial library of pre-built, reusable AI models and assets rather than starting entirely from scratch.. The right choice depends on your project size, budget, and required tech stack.

MobiDev vs Infosys: head-to-head summary

Criterion MobiDev Infosys
Founded 2009 1981
HQ Norcross, USA (delivery centers: Lodz, Poland and Chernivtsi, Ukraine) Bengaluru, India
Team size 201–500 10,000+
Rating 4.3 / 5 3.9 / 5
Best for Small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner. Very large global enterprises wanting a substantial library of pre-built, reusable AI models and assets rather than starting entirely from scratch.
Pricing model Time & Material, Fixed project Not published; enterprise project engagements
Min. engagement Not published Not published
Primary tech stack Python, Computer vision frameworks, Cloud ML platforms Infosys Topaz (proprietary), Topaz Fabric (proprietary), Cloud ML platforms (AWS/Azure/GCP)
Industries served Healthcare, Retail, Manufacturing, Media Banking and financial services, Manufacturing, Retail, Telecommunications

MobiDev vs Infosys: overview

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.

Infosys

Infosys was founded in 1981 in Pune by seven engineers including N.R. Narayana Murthy and Nandan Nilekani, and is headquartered in Bengaluru with more than 330,000 employees worldwide, trading publicly on the NYSE under INFY. Its AI practice, branded Infosys Topaz, reports more than 12,000 AI assets, over 150 pre-trained AI models, and more than ten AI platforms supporting machine learning, generative AI, conversational AI, and intelligent automation work across industry verticals. The company recently launched Topaz Fabric, a composable stack of AI agents, services, and models intended to accelerate enterprise AI investment value.

Services and capabilities: MobiDev vs Infosys

Capability MobiDev Infosys
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: MobiDev vs Infosys

Framework / platform MobiDev Infosys
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 N/A
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: MobiDev vs Infosys

Criterion MobiDev Infosys
Minimum engagement Not published Not published
Engagement models Time & Material, Fixed project, Dedicated team Enterprise project engagement, Managed AI services, Composable agent platform (Topaz Fabric)
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: MobiDev vs Infosys

Dimension MobiDev Infosys
Best company size Startup to mid-market Enterprise
Best industries Healthcare, Retail, Manufacturing Banking and financial services, Manufacturing, Retail
Best use cases 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 Very large enterprises wanting to accelerate AI delivery using a large library of pre-built models and assets, Deploying composable AI agents via the Topaz Fabric platform across multiple business functions
Typical project type Time & Material Enterprise project engagement

MobiDev vs Infosys: pros and cons

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.
Infosys
+ Largest disclosed pre-built AI asset library in this comparison (12,000+ assets, 150+ pre-trained models) can materially speed up delivery.
+ New Topaz Fabric composable AI agent platform reflects continued investment in productized AI tooling.
+ Publicly traded (NYSE: INFY) with more than four decades of operating history and strong financial transparency.
+ Very large global workforce (330,000+) supports substantial multi-region program capacity.
- Specific founding date, headquarters, and team size for the Topaz practice itself are not separately disclosed from the parent company in available public sources.
- No clearly located aggregate Clutch/G2 star rating specific to its AI practice.
- Pricing model and minimum engagement are not published, and typical minimums are substantial for enterprise engagements.
- Heavy reliance on pre-built assets may be less suited to clients needing a fully custom, from-scratch model architecture.

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.

Who should choose Infosys?

Infosys is the right choice for very large global enterprises wanting a substantial library of pre-built, reusable AI models and assets rather than starting entirely from scratch..

Largest disclosed library of reusable, pre-trained AI assets in this comparison (12,000+ assets, 150+ pre-trained models), positioned to accelerate delivery versus fully bespoke builds.. Minimum engagement starts at Not published. Works best with clients in Banking and financial services, Manufacturing, Retail, Telecommunications.

Decision matrix: MobiDev vs Infosys

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 MobiDev
Your budget is at the lower end Compare: MobiDev (Not published) vs Infosys (Not published)
You need specialist depth in a specific vertical MobiDev
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: MobiDev vs Infosys

Use case MobiDev fit Infosys fit Winner
Building a custom ML model for a small or medium-sized business without an internal data science team Strong Limited MobiDev
Combining computer vision or ML work with broader mobile/IoT product development Strong Limited MobiDev
Very large enterprises wanting to accelerate AI delivery using a large library of pre-built models and assets Limited Strong Infosys
Deploying composable AI agents via the Topaz Fabric platform across multiple business functions Limited Strong Infosys
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Limited Limited Both equally

Verdict: MobiDev vs Infosys

MobiDev (4.3/5) is the stronger overall choice for most ML Model Development projects. Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model.. It is best for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..

Infosys (3.9/5) is the better choice when very large global enterprises wanting a substantial library of pre-built, reusable AI models and assets rather than starting entirely from scratch.. If your situation matches those criteria, Infosys is a competitive option.

Related comparisons

MobiDev vs Infosys FAQ

Is MobiDev better than Infosys?

MobiDev (4.3/5) scores higher overall, but "better" depends on your use case. MobiDev is better for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. Infosys is better for very large global enterprises wanting a substantial library of pre-built, reusable AI models and assets rather than starting entirely from scratch..

How do MobiDev and Infosys differ in pricing?

MobiDev uses time & material, fixed project pricing with a minimum engagement of Not published. Infosys uses not published; enterprise project engagements 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: MobiDev or Infosys?

MobiDev 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 MobiDev and Infosys?

MobiDev's primary differentiator is: historical clutch #1 ranking for machine learning development (2021) combined with a specifically sme-oriented service model.. Infosys's primary differentiator is: largest disclosed library of reusable, pre-trained ai assets in this comparison (12,000+ assets, 150+ pre-trained models), positioned to accelerate delivery versus fully bespoke builds.. They also differ in team size (201–500 vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Retail vs Banking and financial services, Manufacturing).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.