Best Machine Learning Development Agencies

EPAM Systems

NYSE-listed global engineering firm with over 60,000 employees and its own enterprise AI orchestration platform.

Founded 1993 | Newtown, Pennsylvania, USA | 10,000+ employees
ml-developmentllm-genaimlopsai-consultingstaff-aug

What is EPAM Systems?

EPAM Systems is a global digital engineering company founded in 1993 by Arkadiy Dobkin and Leo Lozner, listed on the NYSE since 2012, with approximately 62,850 employees as of end of 2025. The company has built a proprietary AI orchestration platform, EPAM DIAL, for managing large language models in production, but AI/ML delivery represents one part of an enormous, broadly diversified enterprise engineering portfolio.

EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, USA. The firm employs 10,000+ people and works primarily with clients in Financial Services, Healthcare, Retail, Technology/SaaS, Government sectors. Its primary differentiator is: Largest headcount on this list (62,000+) with NYSE-listed financial transparency and a proprietary LLM orchestration platform (EPAM DIAL).

EPAM Systems tech stack and services

PythonEPAM DIALAzure OpenAIAWSKubernetes
Service area
Custom ML Development
LLM & Generative AI
MLOps
AI Consulting
Staff Augmentation

EPAM Systems use cases

Short answer: EPAM Systems is best suited for largest global enterprises, AI within a massive engineering partner.

Use case
Global enterprises needing AI delivered at a scale only a 60,000+ employee firm can support
Programs that specifically want to leverage the EPAM DIAL LLM orchestration platform
Highly regulated, multi-country programs needing public-company compliance rigor

EPAM Systems pricing

Short answer: EPAM Systems uses a managed services and fixed project pricing approach. Minimum engagement starts at Not published.

Engagement model Typical range Best for
Managed services Variable; depends on team size Large programmes or team augmentation
Fixed project From Not published Well-defined scope
Staff augmentation Variable; depends on team size Large programmes or team augmentation
EPAM Systems does not publish a public rate card. Contact them directly via their website to get project-specific pricing.

EPAM Systems pros and cons

Advantages Things to consider
+Largest, most globally distributed team on this list, supporting essentially unlimited program scale -AI/ML is a specialization within an enormous generalist engineering portfolio, not the company's defining focus
+NYSE listing (since 2012) provides the highest level of public financial transparency among firms reviewed here -Scale of the organization can translate into higher account-management overhead for smaller engagements
+Proprietary EPAM DIAL platform for LLM orchestration shows real internal AI infrastructure investment -Buyers wanting a boutique, founder-accessible relationship will find that better served by smaller firms on this list
+32 years of continuous operation across more than 55 countries

EPAM Systems vs alternatives

How EPAM Systems compares to the other top Machine Learning Development agencies.

Company Best for Key difference Rating Compare
Neurons Lab Regulated finance firms, PoC-to-production ML delivery. One of the few AI consultancies worldwide holding AWS's Advanced Machine Learning Consulting Competence. 4.8 Full comparison
Tensorway Mid-market companies, full-stack ML plus agentic AI. full-stack ml delivery — data science, mlops, and llm/agentic frameworks (langchain, langgraph, autogen) — in one team. 4.6 Full comparison
Provectus Mid-market and enterprise buyers, AI bundled with cloud... Combines AI/ML delivery with cloud and big-data engineering as a single integrated systems-integrator practice. 4.5 Full comparison
InData Labs Fintech, healthcare, SaaS — specialist data-science boutique. Dedicated in-house R&D center focused specifically on data science and AI rather than broad software outsourcing. 4.5 Full comparison
AI Superior EU SMBs, research-grade ML at accessible pricing. PhD-founder-led team with an explicit research-and-development service line alongside standard client delivery. 4.3 Full comparison
Data Monsters GPU-heavy deep learning, NVIDIA-partnered lab. Elite NVIDIA partnership status supporting GPU-optimized deep learning delivery (per company website; independently unverifiable tier). 4.2 Full comparison
ITRex Group Mid-market companies, AI/ML plus IoT/edge deployment. Explicit focus on applied AI paired with intelligent-edge and IoT development, not just cloud-based ML. 4.2 Full comparison
Ideas2IT Healthcare and BFSI enterprises, AI within product engineering. Employee-ownership model paired with vertical focus in Healthcare, BFSI, and Manufacturing. 4.1 Full comparison
Quantiphi Financial-services enterprises, cloud-native AI at scale. AI-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist IT outsourcing. 4.4 Full comparison
Fractal Analytics Large enterprises, publicly-listed AI/analytics partner. First Indian AI company to complete an IPO (NSE/BSE, February 2026), adding public financial transparency. 4.4 Full comparison
Tredence Retail, CPG, industrials — vertical-focused data science at... Deep vertical focus applying AI specifically within retail, CPG, and industrials contexts rather than horizontal AI consulting. 4.2 Full comparison
Sigmoid Large enterprises, data-engineering-first ML delivery. Data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages. 4.2 Full comparison
LatentView Analytics Companies wanting BI delivery with ML layered in. Publicly listed (NSE/BSE since 2021) analytics firm with two decades of operating history. 3.9 Full comparison
Indium Software Existing Indium QA clients adding AI/ML. Long-standing QA and testing heritage now paired with proprietary AI accelerators like teX.ai. 3.8 Full comparison
Grid Dynamics Enterprises needing SEC-level transparency, AI at scale. Nasdaq-listed public company (GDYN) with SEC-filed financials, offering procurement transparency few competitors match. 4.1 Full comparison
Persistent Systems Very large enterprises, AI from their existing IT... Enterprise-wide scale (24,000+ employees) supporting AI/ML as part of a full IT services portfolio, not a standalone specialty. 3.8 Full comparison
SoftServe Enterprises wanting an established AI/ML, cloud, and IoT... 32 years of continuous operation spanning both a US public-market presence and deep Ukrainian engineering roots. 4.0 Full comparison
N-iX Fortune 500 clients, European-HQ dedicated ML/AI line. 23 years of operating history originating from a Novell technology acquisition, now serving Fortune 500 clients from a Malta-based HQ. 4.0 Full comparison
DataArt Finance, media, healthcare enterprises — established global AI... 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line. 3.9 Full comparison
Andersen Mid-to-large enterprises, AI/ML plus custom software, one vendor. Named AI-powered robotic integration line alongside standard AI/ML and data science services. 4.0 Full comparison
Innowise Group Companies wanting AI/ML within full-cycle software development. Full-cycle software development scope (web, mobile, cloud, QA, security) with AI/ML as one of several integrated specialties. 3.9 Full comparison
Sigma Software Group Companies wanting ML from a top-ranked outsourcing firm. Consecutive annual placement on IAOP's World's Top 100 Outsourcing list every year since 2015. 4.0 Full comparison
Exadel Enterprises, end-to-end model design through MLOps. Explicit end-to-end scope 'from model design to MLOps and integration' as one of five named core service lines. 4.1 Full comparison
MobiDev Retail, hospitality, fitness companies — proven mid-size AI... 65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals. 4.2 Full comparison
Master of Code Global Companies building conversational AI and chatbot products. Specialization narrowly focused on conversational AI and chatbots, with 1,000+ projects delivered over 21 years. 4.1 Full comparison
ScienceSoft Companies wanting AI/ML from an established IT generalist. 36 years of continuous IT consulting history, one of the longest track records among firms on this list. 3.9 Full comparison
Intellectsoft Enterprises wanting AI app development, brand-name client history. Named enterprise client roster (EY, Harley-Davidson, London Stock Exchange, Qualcomm, Jaguar) rare among mid-size firms on this list. 4.0 Full comparison
Belitsoft Small-to-mid companies, affordable AI/ML add-on. 21 years as a custom software development firm now expanding deliberately into generative AI and predictive analytics. 3.9 Full comparison
Neoteric SMBs wanting an accessible generative-AI specialist. 20 years of operating history condensed into a compact, generative-AI-focused team rather than a broad IT services portfolio. 4.3 Full comparison
Addepto Companies wanting boutique AI/BI, now KMS-backed. Boutique AI/BI consultancy that gained additional scale and resources through its December 2025 acquisition by KMS Technology. 4.1 Full comparison
Softweb Solutions Companies needing AI/ML plus IoT, Avnet-backed. Backed by Avnet, a global electronics distributor, giving unusual hardware/IoT supply-chain proximity for AI-on-device projects. 3.9 Full comparison

EPAM Systems FAQ

What is EPAM Systems?

EPAM Systems is a global digital engineering company founded in 1993 by Arkadiy Dobkin and Leo Lozner, listed on the NYSE since 2012, with approximately 62,850 employees as of end of 2025. The company has built a proprietary AI orchestration platform, EPAM DIAL, for managing large language models in production, but AI/ML delivery represents one part of an enormous, broadly diversified enterprise engineering portfolio.

How much does EPAM Systems charge?

EPAM Systems uses managed services and fixed project pricing. Minimum engagement starts at Not published. A discovery call is required to get project-specific quotes.

What tech stack does EPAM Systems use?

EPAM Systems works with Python, EPAM DIAL, Azure OpenAI, AWS, Kubernetes. Primary industries served include Financial Services, Healthcare, Retail, Technology/SaaS, Government.

Is EPAM Systems right for enterprise?

Largest global enterprises, AI within a massive engineering partner. 10,000+ team size. Key consideration: AI/ML is a specialization within an enormous generalist engineering portfolio, not the company's defining focus.

What are the best EPAM Systems alternatives?

The best alternatives to EPAM Systems depend on your use case. Top options are:

  • Neurons Lab: one of the few ai consultancies worldwide holding aws's advanced machine learning consulting competence.
  • Tensorway: full-stack ml delivery — data science, mlops, and llm/agentic frameworks (langchain, langgraph, autogen) — in one team.
  • Provectus: combines ai/ml delivery with cloud and big-data engineering as a single integrated systems-integrator practice.
See full alternatives list

Compare EPAM Systems with other Machine Learning Development agencies