Top Machine Learning Development Companies

Tensorway vs EPAM Systems: full comparison for 2026

Last updated: July 2026

Quick verdict

Tensorway (4.9/5) edges ahead of EPAM Systems (3.8/5) overall. Tensorway is the better choice for mid-market and enterprise teams needing specialist computer vision, time-series, or LLM integration delivered to production. EPAM Systems is the stronger option for global enterprises building complex, software-heavy AI products that require governance, scalability, and a large-team delivery organisation. The right choice depends on your project size, budget, and required tech stack.

Tensorway vs EPAM Systems: head-to-head summary

Criterion Tensorway EPAM Systems
Founded 2023 1993
HQ Valencia, Spain Newtown, PA
Team size 50+ 50,000+
Rating 4.9 / 5 3.8 / 5
Best for Mid-market and enterprise teams needing specialist computer vision, time-series, or LLM integration delivered to production Global enterprises building complex, software-heavy AI products that require governance, scalability, and a large-team delivery organisation
Pricing model Fixed project, retainer Dedicated team, T&M
Min. engagement $30K ~$200K+
Primary tech stack TensorFlow, PyTorch, OpenCV Python, TensorFlow, PyTorch
Industries served Healthcare & Life Sciences, Manufacturing & Industrial, Retail & E-commerce, Financial Services, Media & Entertainment Financial Services, Healthcare & Life Sciences, Manufacturing & Industrial, Media & Entertainment, Retail & E-commerce

Tensorway vs EPAM Systems: overview

Tensorway

Tensorway is a specialist machine learning development company headquartered in Valencia, Spain, backed by Anadea's 25-year enterprise software delivery track record. The firm concentrates on computer vision, time-series forecasting, and LLM integration for mid-market and enterprise clients. A 4.9 Clutch rating reflects consistent delivery quality in production ML systems (per Techreviewer.co). Engagement options include fixed-project and retainer models, with a minimum engagement of $30K.

EPAM Systems

EPAM Systems is a global software engineering and IT services company founded in 1993 and headquartered in Newtown, PA, with 50,000+ professionals. The firm offers AI-native engineering services with a focus on scaling ML, generative AI, and agentic systems across large enterprises with strict governance requirements. EPAM is a powerhouse for building complex, software-heavy AI products from scratch, though it comes at a premium price point.

Services and capabilities: Tensorway vs EPAM Systems

Capability Tensorway EPAM Systems
Custom ML development
Computer vision
NLP & LLMs
MLOps & deployment
Generative AI
Staff augmentation

Tech stack comparison: Tensorway vs EPAM Systems

Framework / platform Tensorway EPAM Systems
TensorFlow
PyTorch
AWS SageMaker N/A N/A
Azure ML N/A N/A
Vertex AI N/A N/A
Scikit-learn N/A N/A
Hugging Face N/A
Apache Spark N/A
Kubernetes N/A
MLflow N/A N/A

Pricing comparison: Tensorway vs EPAM Systems

Criterion Tensorway EPAM Systems
Minimum engagement $30K ~$200K+
Engagement models Fixed project, Retainer Dedicated team, Time & materials
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Enterprise

Target audience comparison: Tensorway vs EPAM Systems

Dimension Tensorway EPAM Systems
Best company size Startup to mid-market Startup to mid-market
Best industries Healthcare & Life Sciences, Manufacturing & Industrial, Retail & E-commerce Financial Services, Healthcare & Life Sciences, Manufacturing & Industrial
Best use cases Object detection and automated quality inspection for manufacturing production lines, Demand and inventory forecasting with time-series ML for retail and logistics Global AI transformation programme for Fortune 100 enterprise with multi-year delivery scope, Enterprise GenAI platform with strict governance and compliance for regulated financial institution
Typical project type Fixed project Dedicated team

Tensorway vs EPAM Systems: pros and cons

Tensorway
+ 4.9 Clutch rating — among the highest verified scores for boutique ML firms
+ Deep computer vision practice covering object detection, pixel segmentation, and real-time video analytics
+ Hybrid time-series approach combining statistical baselines with deep learning layers for superior accuracy
+ Post-deployment model retraining, performance monitoring, and 24/7 support included in retainer scope
+ Enterprise delivery rigour from Anadea's 25-year track record — structured handoffs and documentation
+ Transparent $30K minimum and clear project scoping process reduces discovery ambiguity
- Team size limits simultaneous capacity — large multi-stream programmes may require phased scheduling
- $30K minimum excludes bootstrapped startups with sub-$25K budgets
- Most client case study details remain under NDA — less public proof of scale than larger firms
EPAM Systems
+ 50,000+ professionals — unmatched delivery scale for global multi-stream AI programmes
+ AI-native engineering practice purpose-built for scaling ML, GenAI, and agentic systems
+ Strict governance and compliance frameworks for regulated enterprise AI delivery
+ Full-stack capability from hardware infrastructure through ML models to frontend AI products
+ Strong US and Eastern European delivery mix for cost-performance balance at enterprise scale
- ~$200K+ minimum makes EPAM inaccessible for all but the largest enterprise budgets
- Large-firm overhead — procurement, contracting, and ramp-up timelines are significantly longer than boutiques
- Generalist breadth means less niche ML depth than boutiques in specific domains like healthcare imaging or time-series

Who should choose Tensorway?

Tensorway is the right choice for mid-market and enterprise teams needing specialist computer vision, time-series, or LLM integration delivered to production.

Boutique ML depth combined with Anadea's 25-year enterprise delivery foundation — rare combination in the ML services market. Minimum engagement starts at $30K. Works best with clients in Healthcare & Life Sciences, Manufacturing & Industrial, Retail & E-commerce, Financial Services, Media & Entertainment.

Who should choose EPAM Systems?

EPAM Systems is the right choice for global enterprises building complex, software-heavy AI products that require governance, scalability, and a large-team delivery organisation.

AI-native engineering practice at 50,000-person scale — the broadest talent pool and delivery capacity of any firm on this list. Minimum engagement starts at ~$200K+. Works best with clients in Financial Services, Healthcare & Life Sciences, Manufacturing & Industrial, Media & Entertainment, Retail & E-commerce.

Decision matrix: Tensorway vs EPAM Systems

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Tensorway
You need a large dedicated team for an ongoing programme EPAM Systems
Your budget is at the lower end Tensorway
You need specialist depth in a specific vertical Tensorway
You need staff augmentation or team extension EPAM Systems
You need consulting before committing to a build Both may offer discovery engagements

Use case fit: Tensorway vs EPAM Systems

Use case Tensorway fit EPAM Systems fit Winner
Object detection and automated quality inspection for manufacturing production lines Strong Limited Tensorway
Demand and inventory forecasting with time-series ML for retail and logistics Strong Limited Tensorway
Global AI transformation programme for Fortune 100 enterprise with multi-year delivery scope Limited Strong EPAM Systems
Enterprise GenAI platform with strict governance and compliance for regulated financial institution Strong Strong Both equally
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Tensorway vs EPAM Systems

Tensorway (4.9/5) is the stronger overall choice for most Machine Learning Development projects. Boutique ML depth combined with Anadea's 25-year enterprise delivery foundation — rare combination in the ML services market. It is best for mid-market and enterprise teams needing specialist computer vision, time-series, or LLM integration delivered to production.

EPAM Systems (3.8/5) is the better choice when global enterprises building complex, software-heavy AI products that require governance, scalability, and a large-team delivery organisation. If your situation matches those criteria, EPAM Systems is a competitive option.

Related comparisons

Tensorway vs EPAM Systems FAQ

Is Tensorway better than EPAM Systems?

Tensorway (4.9/5) scores higher overall, but "better" depends on your use case. Tensorway is better for mid-market and enterprise teams needing specialist computer vision, time-series, or LLM integration delivered to production. EPAM Systems is better for global enterprises building complex, software-heavy AI products that require governance, scalability, and a large-team delivery organisation.

How do Tensorway and EPAM Systems differ in pricing?

Tensorway uses fixed project, retainer pricing with a minimum engagement of $30K. EPAM Systems uses dedicated team, t&m pricing with a minimum engagement of ~$200K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Tensorway or EPAM Systems?

EPAM 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 Tensorway and EPAM Systems?

Tensorway's primary differentiator is: boutique ml depth combined with anadea's 25-year enterprise delivery foundation — rare combination in the ml services market. EPAM Systems's primary differentiator is: ai-native engineering practice at 50,000-person scale — the broadest talent pool and delivery capacity of any firm on this list. They also differ in team size (50+ vs 50,000+), minimum engagement ($30K vs ~$200K+), and primary industries served (Healthcare & Life Sciences, Manufacturing & Industrial vs Financial Services, Healthcare & Life Sciences).

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