Best ML Model Development Companies

Tensorway vs EPAM Systems: full comparison for 2026

Quick verdict

Tensorway (4.8/5) edges ahead of EPAM Systems (3.9/5) overall. Tensorway is the better choice for mid-market fintech and SaaS, hybrid forecasting models. EPAM Systems is the stronger option for very large enterprises, proprietary AI orchestration platform. 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 2019 1993
HQ Alicante, Spain Newtown, USA
Team size 51–200 10,000+
Rating 4.8 / 5 3.9 / 5
Primary differentiator Combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in Proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers
Pricing model Time & Material, Fixed-Price PoC, Extended/Dedicated Team, and MVP Development Models Not published; enterprise project engagements
Min. engagement $10,000 Not published
Primary tech stack Python, TensorFlow, PyTorch AWS SageMaker, Amazon Bedrock, EPAM DIAL (proprietary)
Industries served Fintech, Supply chain, Energy, B2B SaaS, Healthcare, Retail Financial services, Life sciences, Media, Travel and hospitality

Tensorway vs EPAM Systems: overview

Tensorway

Tensorway builds and fine-tunes machine learning models for fintech, supply chain, energy, and B2B SaaS clients, with particular depth in hybrid approaches that combine statistical forecasting baselines with deep learning. The company was founded in 2019. Its delivery team spans data scientists, full-stack AI engineers, MLOps specialists, and QA engineers who support the full lifecycle from custom model training through deployment and monitoring. Case studies published on its site include a Named Entity Recognition model for automated Latvian/English invoice processing and a multi-agent deal-sourcing system for an investment firm.

EPAM Systems

EPAM Systems was founded in 1993 in Newtown, Pennsylvania by Arkadiy Dobkin and Leo Lozner, and has grown into a publicly traded (NYSE: EPAM) global engineering company with more than 53,000 employees. EPAM's AI/ML practice includes model development and deployment on Amazon SageMaker and Amazon Bedrock, MLOps, and its proprietary DIAL platform, an enterprise AI orchestration layer. The company was named AWS Global Innovation Partner of the Year in 2025 and holds AWS Premier Tier Services Partner status, reflecting deep hyperscaler-certified delivery capability at very large scale.

Services and capabilities: Tensorway vs EPAM Systems

Capability Tensorway EPAM Systems
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: Tensorway vs EPAM Systems

Framework / platform Tensorway EPAM Systems
PyTorch N/A
TensorFlow N/A
MLflow N/A
AWS SageMaker
Amazon Bedrock N/A
Google Cloud N/A
Microsoft Azure N/A
Kubernetes
Snowflake N/A
NVIDIA N/A

Pricing comparison: Tensorway vs EPAM Systems

Criterion Tensorway EPAM Systems
Minimum engagement $10,000 Not published
Engagement models Dedicated team, Fixed project, Retainer, Time & Material Enterprise project engagement, Managed AI services
Rate transparency $50 - $99 / hr Not public
Price tier Accessible Mid-market

Target audience comparison: Tensorway vs EPAM Systems

Dimension Tensorway EPAM Systems
Best company size Startup to mid-market Enterprise
Best industries Fintech, Supply chain, Energy Financial services, Life sciences, Media
Best use cases Building a hybrid time-series forecasting model for supply chain or energy demand planning, Fine-tuning an NER model for multilingual document/invoice extraction Very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work, Deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer
Typical project type Dedicated team Enterprise project engagement

Tensorway vs EPAM Systems: pros and cons

Tensorway
+ Strong delivery track record in deep learning and NLP, with client references available under NDA
+ Combines statistical and deep-learning methods rather than over-indexing on one approach.
+ Established project-management and QA processes for predictable, well-documented delivery
+ Published, verifiable case studies with concrete outcomes (e.g., NER-based invoice automation).
+ Broad four-tier engagement menu makes it accessible for both PoC-stage and scaling clients.
- Relatively small team (51–200) limits capacity for very large, multi-workstream enterprise programs.
- Published minimum engagement ($10,000) may still require a scoping call to firm up cost for larger projects.
EPAM Systems
+ 2025 AWS Global Innovation Partner of the Year, an independently awarded distinction from AWS itself.
+ Proprietary DIAL orchestration platform provides a differentiated technical asset beyond standard consulting delivery.
+ Publicly traded (NYSE: EPAM) with substantial financial transparency and scale (53,000+ employees).
+ AWS Premier Tier Services Partner status confirms deep, audited hyperscaler certification.
- Very large, generalist software engineering brand means ML/AI is one of many practice areas, not a dedicated specialization.
- 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, and enterprise minimums are typically substantial.
- Named client-specific ML case studies were not clearly surfaced in available search results.

Who should choose Tensorway?

A typical fit: building a hybrid time-series forecasting model for supply chain or energy demand planning.

Combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in. Minimum engagement starts at $10,000. Works best with clients in Fintech, Supply chain, Energy, B2B SaaS, Healthcare, Retail.

Who should choose EPAM Systems?

A typical fit: very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work.

Proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers. Minimum engagement starts at Not published. Works best with clients in Financial services, Life sciences, Media, Travel and hospitality.

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 Tensorway
Your budget is at the lower end Compare: Tensorway ($10,000) vs EPAM Systems (Not published)
You need specialist depth in a specific vertical Tensorway
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
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
Building a hybrid time-series forecasting model for supply chain or energy demand planning Strong Limited Tensorway
Fine-tuning an NER model for multilingual document/invoice extraction Strong Limited Tensorway
Very large enterprises needing an AWS Global Partner of the Year-caliber vendor for ML platform work Limited Strong EPAM Systems
Deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer Limited Strong EPAM Systems
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Limited Strong EPAM Systems

Verdict: Tensorway vs EPAM Systems

Tensorway (4.8/5) is the stronger overall choice for most ML Model Development projects. Combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in.

EPAM Systems (3.9/5) is worth a look if you need deploying models on Amazon SageMaker or Bedrock with EPAM's proprietary DIAL orchestration layer. If your situation matches that, EPAM Systems is a competitive option.

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Tensorway vs EPAM Systems FAQ

Is Tensorway better than EPAM Systems?

Tensorway (4.8/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: strong delivery track record in deep learning and NLP, with client references available under NDA. EPAM Systems's strongest advantage: 2025 AWS Global Innovation Partner of the Year, an independently awarded distinction from AWS itself.

How do Tensorway and EPAM Systems differ in pricing?

Tensorway uses time & material, fixed-price poc, extended/dedicated team, and mvp development models pricing with a minimum engagement of $10,000. EPAM Systems 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: Tensorway or EPAM Systems?

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 EPAM Systems?

Tensorway's primary differentiator is: combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in. EPAM Systems's primary differentiator is: proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers. They also differ in team size (51–200 vs 10,000+), minimum engagement ($10,000 vs Not published), and primary industries served (Fintech, Supply chain vs Financial services, Life sciences).