Best Machine Learning Agencies

Tiger Analytics vs EPAM Systems: full comparison for 2026

Last updated: July 2026

Quick verdict

Tiger Analytics (4.8/5) edges ahead of EPAM Systems (3.9/5) overall. Tiger Analytics is the better choice for fortune 1000 enterprises needing production-grade ML across CPG, BFSI, and healthcare verticals. EPAM Systems is the stronger option for large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering. The right choice depends on your project size, budget, and required tech stack.

Tiger Analytics vs EPAM Systems: head-to-head summary

Criterion Tiger Analytics EPAM Systems
Founded 2011 1993
HQ Santa Clara, CA, USA Newtown, PA, USA
Team size 5,000+ 58,000+
Rating 4.8 / 5 3.9 / 5
Best for Fortune 1000 enterprises needing production-grade ML across CPG, BFSI, and healthcare verticals Large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering
Pricing model T&M, retainer T&M, Dedicated team
Min. engagement $100K $100K
Primary tech stack Python, R, Apache Spark Python, TensorFlow, PyTorch
Industries served Consumer Packaged Goods, Financial Services, Healthcare, Retail / E-commerce, Technology / SaaS, Logistics Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce

Tiger Analytics vs EPAM Systems: overview

Tiger Analytics

Tiger Analytics is a boutique AI and advanced analytics firm founded in 2011 and headquartered in Santa Clara, California, with over 5,000 professionals across the US, Canada, UK, India, Singapore, and Australia. The firm delivers full-stack ML services covering predictive modeling, data engineering, MLOps, NLP, and computer vision, with the deepest bench depth in consumer packaged goods, banking and financial services, healthcare, and retail. Unlike large IT generalists, Tiger Analytics was built specifically around applied data science and machine learning, meaning delivery teams are composed entirely of data scientists, ML engineers, and analytics professionals rather than rotating generalists. Clients include Fortune 1000 corporations seeking to operationalise ML at scale rather than deliver isolated pilots.

EPAM Systems

EPAM Systems is a global digital transformation services company founded in 1993 and headquartered in Newtown, Pennsylvania, with over 58,000 professionals worldwide. It was ranked among the top three tech and AI companies on Glassdoor's Best Places to Work 2026. EPAM's AI and ML practice covers custom ML development, data engineering, generative AI, MLOps, and staff augmentation, delivered across financial services, healthcare, media, SaaS, and logistics. EPAM is best suited to enterprises needing a large-scale delivery partner with the governance, compliance, and programme management infrastructure of a major consultancy at software engineering rates.

Services and capabilities: Tiger Analytics vs EPAM Systems

Capability Tiger Analytics EPAM Systems
Custom ML development
Deep learning
NLP / Text analytics
Computer vision
MLOps & deployment
Generative AI
AI strategy
Staff augmentation
Fixed-price projects
Dedicated team model

Tech stack comparison: Tiger Analytics vs EPAM Systems

Framework / platform Tiger Analytics EPAM Systems
Python
TensorFlow
PyTorch
AWS
Kubernetes N/A
Databricks
MLflow N/A N/A

Pricing comparison: Tiger Analytics vs EPAM Systems

Criterion Tiger Analytics EPAM Systems
Minimum engagement $100K $100K
Engagement models Dedicated team, Time & materials, Retainer Time & materials, Dedicated team
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Tiger Analytics vs EPAM Systems

Dimension Tiger Analytics EPAM Systems
Best company size Startup to mid-market Startup to mid-market
Best industries Consumer Packaged Goods, Financial Services, Healthcare Financial Services, Healthcare, Technology / SaaS
Best use cases Demand forecasting and trade promotion optimisation for CPG enterprises, Credit risk modelling and fraud detection for banking clients Enterprise-scale ML platform build requiring 50+ engineers across data engineering, ML, and MLOps tracks simultaneously, Global digital transformation programmes embedding ML into enterprise software at multiple business units
Typical project type Dedicated team Time & materials

Tiger Analytics vs EPAM Systems: pros and cons

Tiger Analytics
+ Largest specialist bench of any pure-play ML firm — 5,000+ data scientists and ML engineers with no generalist padding
+ Strongest track record in CPG, BFSI, and healthcare with named Fortune 1000 clients across all three verticals
+ Full-stack delivery from raw data engineering through model training, deployment, and ongoing MLOps
+ Global delivery centres enable 24/7 support and competitive blended rates relative to US-only firms
+ Mature MLOps practice with reusable pipelines that reduce time-to-production on repeat project types
+ Strong secondary capability in NLP and computer vision beyond core predictive analytics
- Minimum engagement of $100K makes it inaccessible for early-stage startups or small-scope pilots
- Large team size means senior partners may not be directly involved once a project scales
- Less suitable for niche verticals outside its core CPG/BFSI/healthcare strengths
EPAM Systems
+ 58,000+ engineers provide unmatched concurrent delivery capacity for large-scale enterprise ML programmes
+ Glassdoor top-3 Best Tech & AI Company 2026 reflects high engineering talent quality and retention
+ Full global delivery footprint enables follow-the-sun support and multi-geography data processing compliance
+ Strong programme management and governance infrastructure reduces enterprise delivery risk on complex projects
+ ML capability combined with broader digital transformation services reduces vendor proliferation for enterprise buyers
- $100K minimum and large-firm overhead pricing makes EPAM less suitable for mid-market or startup buyers
- ML specialisation depth is diluted by the breadth of a 58,000-person general technology firm
- Large firm bureaucracy and account management layers can slow decision-making on agile ML projects

Who should choose Tiger Analytics?

Tiger Analytics is the right choice for fortune 1000 enterprises needing production-grade ML across CPG, BFSI, and healthcare verticals.

The largest pure-play ML and advanced analytics specialist with 5,000+ dedicated practitioners across six countries. Minimum engagement starts at $100K. Works best with clients in Consumer Packaged Goods, Financial Services, Healthcare, Retail / E-commerce, Technology / SaaS, Logistics.

Who should choose EPAM Systems?

EPAM Systems is the right choice for large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering.

Global scale with 58,000+ engineers and top-3 Glassdoor AI company ranking — rare ML delivery capacity for simultaneous large enterprise programmes. Minimum engagement starts at $100K. Works best with clients in Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce.

Decision matrix: Tiger Analytics vs EPAM Systems

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 Tiger Analytics
Your budget is at the lower end Tiger Analytics
You need specialist depth in a specific vertical Tiger Analytics
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: Tiger Analytics vs EPAM Systems

Use case Tiger Analytics fit EPAM Systems fit Winner
Demand forecasting and trade promotion optimisation for CPG enterprises Strong Strong Both equally
Credit risk modelling and fraud detection for banking clients Strong Limited Tiger Analytics
Enterprise-scale ML platform build requiring 50+ engineers across data engineering, ML, and MLOps tracks simultaneously Limited Strong EPAM Systems
Global digital transformation programmes embedding ML into enterprise software at multiple business units Limited Strong EPAM Systems
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Strong EPAM Systems

Verdict: Tiger Analytics vs EPAM Systems

Tiger Analytics (4.8/5) is the stronger overall choice for most Machine Learning projects. The largest pure-play ML and advanced analytics specialist with 5,000+ dedicated practitioners across six countries. It is best for fortune 1000 enterprises needing production-grade ML across CPG, BFSI, and healthcare verticals.

EPAM Systems (3.9/5) is the better choice when large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering. If your situation matches those criteria, EPAM Systems is a competitive option.

Related comparisons

Tiger Analytics vs EPAM Systems FAQ

Is Tiger Analytics better than EPAM Systems?

Tiger Analytics (4.8/5) scores higher overall, but "better" depends on your use case. Tiger Analytics is better for fortune 1000 enterprises needing production-grade ML across CPG, BFSI, and healthcare verticals. EPAM Systems is better for large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering.

How do Tiger Analytics and EPAM Systems differ in pricing?

Tiger Analytics uses t&m, retainer pricing with a minimum engagement of $100K. EPAM Systems uses t&m, dedicated team pricing with a minimum engagement of $100K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Tiger Analytics 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 agency before shortlisting.

What are the main differences between Tiger Analytics and EPAM Systems?

Tiger Analytics's primary differentiator is: the largest pure-play ml and advanced analytics specialist with 5,000+ dedicated practitioners across six countries. EPAM Systems's primary differentiator is: global scale with 58,000+ engineers and top-3 glassdoor ai company ranking — rare ml delivery capacity for simultaneous large enterprise programmes. They also differ in team size (5,000+ vs 58,000+), minimum engagement ($100K vs $100K), and primary industries served (Consumer Packaged Goods, Financial Services vs Financial Services, Healthcare).

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