Best Machine Learning Development Agencies

Grid Dynamics vs Persistent Systems: full comparison for 2026

Last updated: July 2026

Quick verdict

Grid Dynamics (4.1/5) edges ahead of Persistent Systems (3.8/5) overall. Grid Dynamics is the better choice for enterprises needing SEC-level financial transparency and public-company compliance alongside AI/ML delivery at scale.. Persistent Systems is the stronger option for very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate.. The right choice depends on your project size, budget, and required tech stack.

Grid Dynamics vs Persistent Systems: head-to-head summary

Criterion Grid Dynamics Persistent Systems
Founded 2006 1990
HQ San Ramon, California, USA Pune, India
Team size 1,001–5,000 10,000+
Rating 4.1 / 5 3.8 / 5
Best for Enterprises needing SEC-level financial transparency and public-company compliance alongside AI/ML delivery at scale. Very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate.
Pricing model Fixed project and managed engineering services Managed services and fixed project
Min. engagement Not published Not published
Primary tech stack Python, TensorFlow, Kubernetes Python, Azure OpenAI, AWS
Industries served Retail, Technology/SaaS, Financial Services, Manufacturing Financial Services, Healthcare, Technology/SaaS, Government

Grid Dynamics vs Persistent Systems: overview

Grid Dynamics

Grid Dynamics Holdings (Nasdaq: GDYN) is an AI-first digital engineering and technology consulting company founded in Silicon Valley in 2006, headquartered in San Ramon, California, with roughly 4,960 employees. As a publicly traded company, it discloses financials via SEC filings, giving buyers an unusual degree of transparency for enterprise procurement and compliance review.

Persistent Systems

Persistent Systems is an Indian multinational technology company founded in 1990 by Anand Deshpande, headquartered in Pune, with roughly 24,600 employees as of March 2025. Its AI/ML offerings, including the Persistent GenAI Hub, sit within a much larger portfolio spanning enterprise software, cloud, and digital engineering services rather than being the company's core specialization.

Services and capabilities: Grid Dynamics vs Persistent Systems

Capability Grid Dynamics Persistent Systems
Custom ML model development
Deep learning & computer vision
NLP & LLM / Generative AI
MLOps & production deployment
Data engineering
AI strategy consulting
Staff augmentation

Tech stack comparison: Grid Dynamics vs Persistent Systems

Framework / platform Grid Dynamics Persistent Systems
Python
TensorFlow N/A
PyTorch N/A N/A
AWS
Azure N/A
Google Cloud N/A
Kubernetes N/A
Databricks N/A N/A
LangChain N/A N/A

Pricing comparison: Grid Dynamics vs Persistent Systems

Criterion Grid Dynamics Persistent Systems
Minimum engagement Not published Not published
Engagement models Fixed project, Managed services Managed services, Fixed project, Staff augmentation
Rate transparency Not public Not public
Price tier Enterprise / not published Enterprise / not published

Target audience comparison: Grid Dynamics vs Persistent Systems

Dimension Grid Dynamics Persistent Systems
Best company size Startup to mid-market Enterprise
Best industries Retail, Technology/SaaS, Financial Services Financial Services, Healthcare, Technology/SaaS
Best use cases Enterprise buyers requiring public-company financial transparency for vendor risk review, Retail and e-commerce AI/ML programs at large scale Enterprises already using Persistent for core IT services wanting to add AI/ML from the same vendor, Very large, multi-year digital transformation programs where AI is one workstream among many
Typical project type Fixed project Managed services

Grid Dynamics vs Persistent Systems: pros and cons

Grid Dynamics
+ Public-company status (Nasdaq: GDYN) means audited financials are publicly available for vendor risk assessment
+ AI-first branding since founding, rather than a later pivot from generalist outsourcing
+ Nearly 5,000 employees supports large, multi-region enterprise engagements
+ 19 years of continuous operation under stable leadership
- Public-company scale and process can mean slower sales cycles than boutique specialists
- Broad digital-engineering positioning means ML-specific depth is one part of a wider service catalog
- Minimum engagement size not publicly disclosed
Persistent Systems
+ 35 years of operating history and one of the largest headcounts on this list (24,000+)
+ AI capability delivered alongside a company's existing broader IT services relationship, reducing vendor sprawl
+ 16,000+ AI-trained staff cited internally, suggesting significant AI upskilling investment (per company website)
+ Public-company scale supports very large, multi-year enterprise transformation programs
- AI/ML is one offering within a much larger, more generalist IT services portfolio rather than the firm's core focus
- Buyers seeking cutting-edge ML specialization may find deeper expertise at AI-first boutiques on this list
- Very large organization can mean slower response times and more layered account management than smaller firms

Who should choose Grid Dynamics?

Grid Dynamics is the right choice for enterprises needing SEC-level financial transparency and public-company compliance alongside AI/ML delivery at scale..

Nasdaq-listed public company (GDYN) with SEC-filed financials, offering procurement transparency few competitors match.. Minimum engagement starts at Not published. Works best with clients in Retail, Technology/SaaS, Financial Services, Manufacturing.

Who should choose Persistent Systems?

Persistent Systems is the right choice for very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate..

Enterprise-wide scale (24,000+ employees) supporting AI/ML as part of a full IT services portfolio, not a standalone specialty.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Healthcare, Technology/SaaS, Government.

Decision matrix: Grid Dynamics vs Persistent Systems

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Grid Dynamics
You need a large dedicated team for an ongoing programme Check each company's engagement model
Your budget is at the lower end Compare: Grid Dynamics (Not published) vs Persistent Systems (Not published)
You need specialist depth in a specific vertical Grid Dynamics
You need staff augmentation or team extension Persistent Systems
You need consulting before committing to a build Grid Dynamics

Use case fit: Grid Dynamics vs Persistent Systems

Use case Grid Dynamics fit Persistent Systems fit Winner
Enterprise buyers requiring public-company financial transparency for vendor risk review Strong Strong Both equally
Retail and e-commerce AI/ML programs at large scale Strong Limited Grid Dynamics
Enterprises already using Persistent for core IT services wanting to add AI/ML from the same vendor Limited Strong Persistent Systems
Very large, multi-year digital transformation programs where AI is one workstream among many Strong Strong Both equally
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Grid Dynamics vs Persistent Systems

Grid Dynamics (4.1/5) is the stronger overall choice for most Machine Learning Development projects. Nasdaq-listed public company (GDYN) with SEC-filed financials, offering procurement transparency few competitors match.. It is best for enterprises needing SEC-level financial transparency and public-company compliance alongside AI/ML delivery at scale..

Persistent Systems (3.8/5) is the better choice when very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate.. If your situation matches those criteria, Persistent Systems is a competitive option.

Related comparisons

Grid Dynamics vs Persistent Systems FAQ

Is Grid Dynamics better than Persistent Systems?

Grid Dynamics (4.1/5) scores higher overall, but "better" depends on your use case. Grid Dynamics is better for enterprises needing SEC-level financial transparency and public-company compliance alongside AI/ML delivery at scale.. Persistent Systems is better for very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate..

How do Grid Dynamics and Persistent Systems differ in pricing?

Grid Dynamics uses fixed project and managed engineering services pricing with a minimum engagement of Not published. Persistent Systems uses managed services and fixed project 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: Grid Dynamics or Persistent Systems?

Grid Dynamics 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 Grid Dynamics and Persistent Systems?

Grid Dynamics's primary differentiator is: nasdaq-listed public company (gdyn) with sec-filed financials, offering procurement transparency few competitors match.. Persistent Systems's primary differentiator is: enterprise-wide scale (24,000+ employees) supporting ai/ml as part of a full it services portfolio, not a standalone specialty.. They also differ in team size (1,001–5,000 vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Retail, Technology/SaaS vs Financial Services, Healthcare).

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