Persistent Systems vs Globant: full comparison for 2026
Last updated: July 2026
Quick verdict
Persistent Systems (3.9/5) edges ahead of Globant (3.9/5) overall. Persistent Systems is the better choice for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators.. Globant is the stronger option for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.. The right choice depends on your project size, budget, and required tech stack.
Persistent Systems vs Globant: head-to-head summary
| Criterion | Persistent Systems | Globant |
|---|---|---|
| Founded | 1990 | 2003 |
| HQ | Pune, India | Luxembourg City, Luxembourg |
| Team size | 10,000+ | 10,000+ |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Best for | Mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators. | Large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting. |
| Pricing model | Not published; enterprise project engagements | Not published; moving toward subscription-style pricing for AI Pods (per third-party commentary; independently unverifiable in detail) |
| Min. engagement | Not published | Not published |
| Primary tech stack | AWS, Microsoft Azure, Google Cloud | Proprietary Glob.AI OS platform, Computer vision (via Synthesis AI partnership), Cloud ML platforms |
| Industries served | Healthcare, Financial services, Technology/software, Life sciences | Financial services, Life sciences, Airlines/travel, Sports and entertainment |
Persistent Systems vs Globant: overview
Persistent Systems
Persistent Systems Limited was founded in 1990 in Pune, India, by Dr. Anand Deshpande, and has grown into a publicly traded (NSE/BSE: PERSISTENT) multinational technology services company with more than 24,000 employees. Its Data Science and Machine Learning practice spans data engineering through enterprise ML deployment across AWS, Azure, and Google Cloud, supported by its Data Experience Hub (DxH), a set of accelerators aimed at operationalizing ML and detecting bias in models through explainable AI. Persistent was named a Leader in the Everest Group Data & AI PEAK Matrix 2025 for the mid-market segment, and holds AWS Premier Tier Partner and Google Cloud Data & Analytics plus Machine Learning Specializations.
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.
Services and capabilities: Persistent Systems vs Globant
| Capability | Persistent Systems | Globant |
|---|---|---|
| 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: Persistent Systems vs Globant
| Framework / platform | Persistent Systems | Globant |
|---|---|---|
| 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 |
| Microsoft Azure | ✓ | N/A |
| Kubernetes | N/A | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: Persistent Systems vs Globant
| Criterion | Persistent Systems | Globant |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Enterprise project engagement, Managed AI services | Studio-based engagement, Enterprise project engagement, Subscription (AI Pods) |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Persistent Systems vs Globant
| Dimension | Persistent Systems | Globant |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Healthcare, Financial services, Technology/software | Financial services, Life sciences, Airlines/travel |
| Best use cases | Operationalizing ML models at enterprise scale using pre-built MLOps accelerators, Running bias detection and explainable AI reviews on existing production models | Large enterprises wanting pre-packaged, industry-specific AI solutions delivered quickly via studio teams, Sports, entertainment, or media companies exploring agentic AI applications |
| Typical project type | Enterprise project engagement | Studio-based engagement |
Persistent Systems vs Globant: pros and cons
| Persistent Systems | |
|---|---|
| + | Everest Group Leader ranking in the Data & AI PEAK Matrix 2025 (mid-market segment) is an independently sourced third-party validation. |
| + | Purpose-built DxH accelerators for MLOps and bias detection add concrete, named tooling beyond generic claims. |
| + | Publicly traded with 35-year operating history, providing financial transparency. |
| + | Named healthcare client work (e.g., cancer-detection collaboration) with a specific, checkable use case. |
| - | Very large scale (24,000+ employees) means ML/AI is one of several major practice areas competing for delivery focus. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its AI practice in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | India-centric delivery model may require additional coordination for clients preferring more localized teams. |
| 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. |
Who should choose Persistent Systems?
Persistent Systems is the right choice for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators..
Purpose-built DxH accelerator suite for MLOps and bias detection, plus a specific Everest Group Leader ranking in the mid-market Data & AI segment rather than only the largest enterprise tier.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Financial services, Technology/software, Life sciences.
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.
Decision matrix: Persistent Systems vs Globant
| 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: Persistent Systems (Not published) vs Globant (Not published) |
| You need specialist depth in a specific vertical | Persistent Systems |
| 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: Persistent Systems vs Globant
| Use case | Persistent Systems fit | Globant fit | Winner |
|---|---|---|---|
| Operationalizing ML models at enterprise scale using pre-built MLOps accelerators | Strong | Limited | Persistent Systems |
| Running bias detection and explainable AI reviews on existing production models | Strong | Limited | Persistent Systems |
| Large enterprises wanting pre-packaged, industry-specific AI solutions delivered quickly via studio teams | Limited | Strong | Globant |
| Sports, entertainment, or media companies exploring agentic AI applications | Limited | Strong | Globant |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Limited | Persistent Systems |
Verdict: Persistent Systems vs Globant
Persistent Systems (3.9/5) is the stronger overall choice for most ML Model Development projects. Purpose-built DxH accelerator suite for MLOps and bias detection, plus a specific Everest Group Leader ranking in the mid-market Data & AI segment rather than only the largest enterprise tier.. It is best for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators..
Globant (3.9/5) is the better choice when large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.. If your situation matches those criteria, Globant is a competitive option.
Related comparisons
Persistent Systems vs Globant FAQ
Is Persistent Systems better than Globant?
Persistent Systems (3.9/5) scores higher overall, but "better" depends on your use case. Persistent Systems is better for mid-market and enterprise buyers wanting a publicly traded, multi-cloud certified partner with pre-built MLOps and explainable-AI accelerators.. 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..
How do Persistent Systems and Globant differ in pricing?
Persistent Systems uses not published; enterprise project engagements pricing with a minimum engagement of Not published. 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. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Persistent Systems or Globant?
Persistent Systems 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 Persistent Systems and Globant?
Persistent Systems's primary differentiator is: purpose-built dxh accelerator suite for mlops and bias detection, plus a specific everest group leader ranking in the mid-market data & ai segment rather than only the largest enterprise tier.. 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.. They also differ in team size (10,000+ vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Financial services vs Financial services, Life sciences).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.