Globant vs Infosys: full comparison for 2026
Last updated: July 2026
Quick verdict
Globant (3.9/5) edges ahead of Infosys (3.9/5) overall. Globant is the better choice for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.. 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.
Globant vs Infosys: head-to-head summary
| Criterion | Globant | Infosys |
|---|---|---|
| Founded | 2003 | 1981 |
| HQ | Luxembourg City, Luxembourg | Bengaluru, India |
| Team size | 10,000+ | 10,000+ |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Best for | Large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting. | Very large global enterprises wanting a substantial library of pre-built, reusable AI models and assets rather than starting entirely from scratch. |
| Pricing model | Not published; moving toward subscription-style pricing for AI Pods (per third-party commentary; independently unverifiable in detail) | Not published; enterprise project engagements |
| Min. engagement | Not published | Not published |
| Primary tech stack | Proprietary Glob.AI OS platform, Computer vision (via Synthesis AI partnership), Cloud ML platforms | Infosys Topaz (proprietary), Topaz Fabric (proprietary), Cloud ML platforms (AWS/Azure/GCP) |
| Industries served | Financial services, Life sciences, Airlines/travel, Sports and entertainment | Banking and financial services, Manufacturing, Retail, Telecommunications |
Globant vs Infosys: overview
Globant
Globant was founded in 2003 in Buenos Aires by Martin Migoya, Guibert Englebienne, Martin Umaran, and Nestor Nocetti, and is now headquartered in Luxembourg while trading publicly on the NYSE under GLOB. The company reports roughly 29,000 employees and organizes its AI capability around eight industry-specific studios that produce what it calls "AI Pods," tailored solutions for specific industry challenges spanning financial services, life sciences, and airlines among others. Globant was recognized by IDC MarketScape as a Worldwide Leader in AI Services in 2023, and has named client work including LALIGA for agentic AI in sports, presented at NVIDIA GTC 2026.
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: Globant vs Infosys
| Capability | Globant | 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: Globant vs Infosys
| Framework / platform | Globant | 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 | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: Globant vs Infosys
| Criterion | Globant | Infosys |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Studio-based engagement, Enterprise project engagement, Subscription (AI Pods) | 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: Globant vs Infosys
| Dimension | Globant | Infosys |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Financial services, Life sciences, Airlines/travel | Banking and financial services, Manufacturing, Retail |
| Best use cases | Large enterprises wanting pre-packaged, industry-specific AI solutions delivered quickly via studio teams, Sports, entertainment, or media companies exploring agentic AI applications | 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 | Studio-based engagement | Enterprise project engagement |
Globant vs Infosys: pros and cons
| Globant | |
|---|---|
| + | IDC MarketScape Worldwide Leader in AI Services (2023), an independently sourced third-party analyst validation. |
| + | Named, checkable client work (LALIGA agentic AI, presented publicly at NVIDIA GTC 2026). |
| + | Industry-specific studio model can accelerate time-to-value versus fully custom engagements. |
| + | Publicly traded (NYSE: GLOB) with substantial scale (29,000+ employees). |
| - | Studio/Pod delivery model provides less MLOps/infrastructure-specific documented depth than peers like EPAM or Persistent. |
| - | No clearly located aggregate Clutch/G2 star rating in available public sources. |
| - | Pricing details, including the reported move to subscription models, are not fully independently verifiable. |
| - | Large scale means individual client attention may vary depending on which studio is engaged. |
| 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 Globant?
Globant is the right choice for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting..
Only company in this list organized around a formal "studio + AI Pods" delivery model, and the only one with an IDC MarketScape Worldwide Leader in AI Services designation.. Minimum engagement starts at Not published. Works best with clients in Financial services, Life sciences, Airlines/travel, Sports and entertainment.
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: Globant vs Infosys
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Check each company's engagement model |
| Your budget is at the lower end | Compare: Globant (Not published) vs Infosys (Not published) |
| You need specialist depth in a specific vertical | Globant |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Globant |
Use case fit: Globant vs Infosys
| Use case | Globant fit | Infosys fit | Winner |
|---|---|---|---|
| Large enterprises wanting pre-packaged, industry-specific AI solutions delivered quickly via studio teams | Strong | Strong | Both equally |
| Sports, entertainment, or media companies exploring agentic AI applications | Strong | Limited | Globant |
| 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: Globant vs Infosys
Globant (3.9/5) is the stronger overall choice for most ML Model Development projects. Only company in this list organized around a formal "studio + AI Pods" delivery model, and the only one with an IDC MarketScape Worldwide Leader in AI Services designation.. It is best for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting..
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
Globant vs Infosys FAQ
Is Globant better than Infosys?
Globant (3.9/5) scores higher overall, but "better" depends on your use case. Globant is better for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.. 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 Globant and Infosys differ in pricing?
Globant uses not published; moving toward subscription-style pricing for ai pods (per third-party commentary; independently unverifiable in detail) 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: Globant or Infosys?
Globant 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 Globant and Infosys?
Globant's primary differentiator is: only company in this list organized around a formal "studio + ai pods" delivery model, and the only one with an idc marketscape worldwide leader in ai services designation.. 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 (10,000+ vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Life sciences vs Banking and financial services, Manufacturing).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.