Tensorway vs Globant: full comparison for 2026
Quick verdict
Tensorway (4.4/5) edges ahead of Globant (4.1/5) overall. Tensorway is the better choice for product teams adding senior AI specialists without vendor lock-in. Globant is the stronger option for enterprises wanting AI capacity on a subscription model. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs Globant: head-to-head summary
| Criterion | Tensorway | Globant |
|---|---|---|
| Founded | 2019 | 2003 |
| HQ | Alicante, Spain | Luxembourg |
| Team size | 50–249 | 28,000+ |
| Rating | 4.4 / 5 | 4.1 / 5 |
| Primary differentiator | Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories | Subscription-based AI Pods as an alternative to per-engineer billing |
| Pricing model | Monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request | AI Pods monthly subscription with token-based capacity; staff augmentation and SOW contracts; rates on request |
| Min. engagement | Not disclosed | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, OpenAI, Azure ML |
| Industries served | Financial services, Software & SaaS, Healthcare & life sciences, Logistics, Manufacturing | Media, Financial services, Travel, Retail & e-commerce, Healthcare & life sciences |
Tensorway vs Globant: overview
Tensorway
Tensorway, founded in 2019 and based in Alicante, Spain, supplies AI engineers who join a client's own team and work inside its Slack, Jira and version control under its coding standards. The firm has more than 20 years of software engineering practice behind its delivery methods. Its central promise concerns ownership: code, documentation and trained models stay in the client's repositories, and knowledge transfer to in-house staff is part of every engagement (per company website; independently unverifiable). Available roles include LLM engineers, RAG specialists, MLOps architects, computer-vision and NLP engineers, with teams usually starting as a squad of two to five. In one published case, a U.S. trading platform serving more than 100,000 investors reports 40% faster market-data processing and 35% lower operating costs (per company website; independently unverifiable).
Globant
Globant was founded in Buenos Aires in 2003 and is now headquartered in Luxembourg. The NYSE-listed company reported 28,773 employees at the end of 2025. In 2025 it launched AI Pods, a monthly subscription for AI-assisted engineering capacity metered by tokens. Third-party reviews say classic staff augmentation runs mainly through Belatrix, a firm Globant acquired, while large accounts usually buy managed pods or statements of work.
Services and capabilities: Tensorway vs Globant
| Capability | Tensorway | Globant |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps & deployment | ✓ | ✗ |
| Computer vision | ✓ | ✗ |
| Data engineering | ✗ | ✓ |
| AI agent development | ✗ | ✓ |
| Fractional / part-time experts | ✓ | ✗ |
| Risk-free trial period | ✓ | ✗ |
| Nearshore time-zone overlap | ✗ | ✓ |
Tech stack comparison: Tensorway vs Globant
| Framework / platform | Tensorway | Globant |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Databricks | N/A | ✓ |
| MLflow | ✓ | N/A |
| Kubernetes | ✓ | ✓ |
Pricing comparison: Tensorway vs Globant
| Criterion | Tensorway | Globant |
|---|---|---|
| Minimum engagement | Not disclosed | Not published |
| Engagement models | Full-time dedicated engineers, Part-time fractional experts, Trial period | Dedicated team, Managed delivery, Full-time dedicated engineers |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Tensorway vs Globant
| Dimension | Tensorway | Globant |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Software & SaaS, Healthcare & life sciences | Media, Financial services, Travel |
| Best use cases | Adding RAG and evaluation expertise to a SaaS team shipping its first LLM feature, Bringing GPU inference costs under control for a production model | Buying a monthly AI engineering pod for a marketing-tech roadmap, Staffing agent development across several brands |
| Typical project type | Full-time dedicated engineers | Dedicated team |
Tensorway vs Globant: pros and cons
| Tensorway | |
|---|---|
| + | Candidates pass a code review, a practical task in their specialty and a communication check run by senior AI engineers |
| + | Clients keep all code, documentation and trained models in their own repositories |
| + | First engineer typically starts in one to two weeks and a full squad in three to four (per company website; independently unverifiable) |
| + | Engineers bring GPU and inference cost control, fine-tuning and vector-database experience |
| + | Commitment is monthly and can be adjusted between sprints, with no-cost replacement for a poor fit |
| - | No public rate card, so budgeting starts with a sales call |
| - | Its bench is far smaller than EPAM's or Turing's, which limits how many engineers can start at once |
| - | Only AI and ML roles are offered, so general full-stack or QA staffing has to come from elsewhere |
| Globant | |
|---|---|
| + | AI Pods give finance teams a predictable monthly cost |
| + | Large Latin American delivery footprint on U.S.-friendly hours |
| + | Public-company governance suits procurement-heavy buyers |
| - | Individual staff augmentation is a side channel run largely through the acquired Belatrix business |
| - | Headcount fell about 8% during 2025, according to Bloomberg Línea |
| - | Pod and token-based pricing is hard to compare with per-engineer quotes |
Who should choose Tensorway?
A typical fit: adding RAG and evaluation expertise to a SaaS team shipping its first LLM feature.
Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Software & SaaS, Healthcare & life sciences, Logistics, Manufacturing.
Who should choose Globant?
A typical fit: buying a monthly AI engineering pod for a marketing-tech roadmap.
Subscription-based AI Pods as an alternative to per-engineer billing. Minimum engagement is not publicly disclosed. Works best with clients in Media, Financial services, Travel, Retail & e-commerce, Healthcare & life sciences.
Decision matrix: Tensorway vs Globant
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Globant |
| You want the supplier to own delivery as well as staffing | Globant |
| You need one expert part-time | Tensorway |
| You want to test an engineer before signing for months | Tensorway |
| Your budget is at the lower end | Compare: Tensorway (Not disclosed) vs Globant (Not published) |
| You need overlap with U.S. working hours | Globant |
| You need specialist depth in a specific vertical | Tensorway |
Use case fit: Tensorway vs Globant
| Use case | Tensorway fit | Globant fit | Winner |
|---|---|---|---|
| Adding RAG and evaluation expertise to a SaaS team shipping its first LLM feature | Strong | Limited | Tensorway |
| Bringing GPU inference costs under control for a production model | Strong | Limited | Tensorway |
| Buying a monthly AI engineering pod for a marketing-tech roadmap | Limited | Strong | Globant |
| Staffing agent development across several brands | Strong | Strong | Both equally |
Verdict: Tensorway vs Globant
Tensorway (4.4/5) is the stronger overall choice for most AI Staff Augmentation projects. Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories.
Globant (4.1/5) is worth a look if you need staffing agent development across several brands. If your situation matches that, Globant is a competitive option.
Related comparisons
Tensorway vs Globant FAQ
Is Tensorway better than Globant?
Tensorway (4.4/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: candidates pass a code review, a practical task in their specialty and a communication check run by senior AI engineers. Globant's strongest advantage: AI Pods give finance teams a predictable monthly cost.
How do Tensorway and Globant differ in pricing?
Tensorway uses monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request pricing. Globant uses ai pods monthly subscription with token-based capacity; staff augmentation and sow contracts; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or Globant?
Tensorway 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 Tensorway and Globant?
Tensorway's primary differentiator is: senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories. Globant's primary differentiator is: subscription-based AI Pods as an alternative to per-engineer billing. They also differ in team size (50–249 vs 28,000+), minimum engagement (Not disclosed vs Not published), and primary industries served (Financial services, Software & SaaS vs Media, Financial services).
Verify all details directly with each company before making a decision.