InData Labs vs Globant: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.3/5) edges ahead of Globant (3.9/5) overall. InData Labs is the better choice for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks.. 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.
InData Labs vs Globant: head-to-head summary
| Criterion | InData Labs | Globant |
|---|---|---|
| Founded | 2014 | 2003 |
| HQ | Nicosia, Cyprus (delivery center: Minsk, Belarus) | Luxembourg City, Luxembourg |
| Team size | 51–200 | 10,000+ |
| Rating | 4.3 / 5 | 3.9 / 5 |
| Best for | Companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks. | Large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting. |
| Pricing model | Project-based | Not published; moving toward subscription-style pricing for AI Pods (per third-party commentary; independently unverifiable in detail) |
| Min. engagement | $25,000 | Not published |
| Primary tech stack | Python, Computer vision frameworks, NLP toolkits | Proprietary Glob.AI OS platform, Computer vision (via Synthesis AI partnership), Cloud ML platforms |
| Industries served | Transportation/logistics, Retail, Finance | Financial services, Life sciences, Airlines/travel, Sports and entertainment |
InData Labs vs Globant: overview
InData Labs
InData Labs is a data science consultancy founded in 2014 by Marat Karpeko, with a registered headquarters in Nicosia, Cyprus, and its primary research and development center in Minsk, Belarus. The company focuses on predictive analytics, natural language processing, and computer vision, delivering custom AI model development for clients ranging from logistics to retail. Published case studies include a freight-rate prediction model for a transportation company and a dog-face-identification model reporting 91.96 percent accuracy, giving it more quantified, checkable outcome data than many peers of similar size.
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: InData Labs vs Globant
| Capability | InData Labs | 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: InData Labs vs Globant
| Framework / platform | InData Labs | 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 | 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: InData Labs vs Globant
| Criterion | InData Labs | Globant |
|---|---|---|
| Minimum engagement | $25,000 | Not published |
| Engagement models | Fixed project, Time & Material | Studio-based engagement, Enterprise project engagement, Subscription (AI Pods) |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs Globant
| Dimension | InData Labs | Globant |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Transportation/logistics, Retail, Finance | Financial services, Life sciences, Airlines/travel |
| Best use cases | Building a predictive pricing or demand-forecasting model for logistics or transportation, Developing a computer-vision classification model with a documented accuracy target | 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 | Fixed project | Studio-based engagement |
InData Labs vs Globant: pros and cons
| InData Labs | |
|---|---|
| + | Case studies include specific, quantified model accuracy figures rather than vague outcome claims. |
| + | Featured among Clutch's broader provider directory with a positive review sentiment on delivery timeliness. |
| + | Focused specialization in predictive analytics and computer vision avoids service-line dilution. |
| + | Recognized in a 2016 "Top 100 Big Data" listing, indicating an established track record. |
| - | Team size figures are inconsistent across sources (roughly 50–80 depending on source), so exact headcount is uncertain. |
| - | Registered HQ (Cyprus) differs from the primary delivery center (Belarus), which some buyers may want clarified given regional considerations. |
| - | Public tech-stack disclosure is limited beyond high-level specialization areas. |
| - | Fewer large, brand-name enterprise clients named publicly compared to bigger peers. |
| 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 InData Labs?
InData Labs is the right choice for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks..
Publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims.. Minimum engagement starts at $25,000. Works best with clients in Transportation/logistics, Retail, Finance.
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: InData Labs vs Globant
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | InData Labs |
| You need a large dedicated team for an ongoing programme | Check each company's engagement model |
| Your budget is at the lower end | Compare: InData Labs ($25,000) vs Globant (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: InData Labs vs Globant
| Use case | InData Labs fit | Globant fit | Winner |
|---|---|---|---|
| Building a predictive pricing or demand-forecasting model for logistics or transportation | Strong | Limited | InData Labs |
| Developing a computer-vision classification model with a documented accuracy target | Strong | Limited | InData Labs |
| 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 | Limited | Strong | Globant |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Limited | Limited | Both equally |
Verdict: InData Labs vs Globant
InData Labs (4.3/5) is the stronger overall choice for most ML Model Development projects. Publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims.. It is best for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks..
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.
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InData Labs vs Globant FAQ
Is InData Labs better than Globant?
InData Labs (4.3/5) scores higher overall, but "better" depends on your use case. InData Labs is better for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks.. 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 InData Labs and Globant differ in pricing?
InData Labs uses project-based pricing with a minimum engagement of $25,000. 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: InData Labs or Globant?
InData Labs 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 InData Labs and Globant?
InData Labs's primary differentiator is: publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims.. 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 (51–200 vs 10,000+), minimum engagement ($25,000 vs Not published), and primary industries served (Transportation/logistics, Retail vs Financial services, Life sciences).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.