Top AI Development Agencies

Grid Dynamics vs Belitsoft: full comparison for 2026

Quick verdict

Grid Dynamics (4.1/5) edges ahead of Belitsoft (4.0/5) overall. Grid Dynamics is the better choice for enterprises wanting a publicly-audited AI engineering partner. Belitsoft is the stronger option for teams wanting AI from an established staff augmentation partner. The right choice depends on your project size, budget, and required tech stack.

Grid Dynamics vs Belitsoft: head-to-head summary

Criterion Grid Dynamics Belitsoft
Founded 2006 2004
HQ San Ramon, United States Warsaw, Poland
Team size 4,800+ 250-400
Rating 4.1 / 5 4.0 / 5
Primary differentiator Nasdaq listing (GDYN) with quarterly financial disclosure Twenty years of outsourcing delivery with AI added as a distinctly recent practice
Pricing model Dedicated team or retainer Dedicated team or staff augmentation
Min. engagement Not disclosed Not disclosed
Primary tech stack Python, AWS, Azure Python, AWS, .NET
Industries served Retail & e-commerce, Financial services, Manufacturing, Telecom Healthcare, Fintech, E-learning

Grid Dynamics vs Belitsoft: overview

Grid Dynamics

Grid Dynamics has traded on Nasdaq as GDYN since March 2020, well over a decade after its 2006 founding. As of mid-2026 it reported approximately 4,838 personnel across the US, UK, the Netherlands, Mexico, Switzerland, and Central and Eastern Europe. AI-powered digital engineering is marketed as a core practice, and public-company status gives enterprise buyers financial visibility most agencies on this list can't offer.

Belitsoft

Belitsoft was founded in 2004 and is headquartered in Warsaw, Poland, with over 250 core employees and more than 400 developers, testers, project managers, and DevOps staff distributed across Poland, Latvia, and Georgia. The company expanded into cloud and AI development in 2024, layering AI software solutions on top of an already-established web and mobile development and team augmentation business. That makes AI a genuinely recent addition rather than a rebrand of older services.

Services and capabilities: Grid Dynamics vs Belitsoft

Capability Grid Dynamics Belitsoft
Generative AI
Machine learning
AI agents
MLOps
AI consulting
Fixed-price projects
Dedicated team model

Tech stack comparison: Grid Dynamics vs Belitsoft

Framework / platform Grid Dynamics Belitsoft
Python
PyTorch N/A N/A
TensorFlow N/A N/A
LangChain N/A N/A
AWS
Azure N/A
Kubernetes N/A

Pricing comparison: Grid Dynamics vs Belitsoft

Criterion Grid Dynamics Belitsoft
Minimum engagement Not disclosed Not disclosed
Engagement models Dedicated team, Retainer Dedicated team, Staff augmentation
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Grid Dynamics vs Belitsoft

Dimension Grid Dynamics Belitsoft
Best company size Startup to mid-market Startup to mid-market
Best industries Retail & e-commerce, Financial services, Manufacturing Healthcare, Fintech, E-learning
Best use cases Standing up MLOps infrastructure to move models from pilot into reliable production., Running an enterprise AI program that needs public-company financial due diligence. Augmenting an internal team with AI engineers on a staff-aug basis., Working with an established outsourcing partner that's newly investing in AI capability.
Typical project type Dedicated team Dedicated team

Grid Dynamics vs Belitsoft: pros and cons

Grid Dynamics
+ Nasdaq listing gives enterprise procurement direct access to audited financial statements.
+ Delivery footprint spans North America, Europe, and Latin America.
+ Nearly 5,000 personnel supports several concurrent large AI programs.
+ MLOps and data engineering depth supports production, not just pilot, AI systems.
- Scale and public-company overhead tend to push minimum engagement sizes above boutique-firm levels
- AI operates inside a broader digital engineering portfolio rather than as its own standalone identity
Belitsoft
+ Two decades of outsourcing and staff augmentation experience across Poland, Latvia, and Georgia.
+ Transparent about AI being a 2024 addition rather than overstating a longer AI history.
+ Over 400 combined technical staff supports flexible team augmentation.
+ Established e-learning industry presence gives it relevant vertical experience.
- AI practice is genuinely new as of 2024, with a shorter track record than most on this list
- AI sits alongside a broader outsourcing business rather than as the firm's core identity

Who should choose Grid Dynamics?

A typical fit: standing up MLOps infrastructure to move models from pilot into reliable production.

Nasdaq listing (GDYN) with quarterly financial disclosure. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Financial services, Manufacturing, Telecom.

Who should choose Belitsoft?

A typical fit: augmenting an internal team with AI engineers on a staff-aug basis.

Twenty years of outsourcing delivery with AI added as a distinctly recent practice. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Fintech, E-learning.

Decision matrix: Grid Dynamics vs Belitsoft

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 Grid Dynamics
Your budget is at the lower end Compare: Grid Dynamics (Not disclosed) vs Belitsoft (Not disclosed)
You need specialist depth in a specific vertical Grid Dynamics
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Belitsoft

Use case fit: Grid Dynamics vs Belitsoft

Use case Grid Dynamics fit Belitsoft fit Winner
Standing up MLOps infrastructure to move models from pilot into reliable production. Strong Limited Grid Dynamics
Running an enterprise AI program that needs public-company financial due diligence. Strong Limited Grid Dynamics
Augmenting an internal team with AI engineers on a staff-aug basis. Limited Strong Belitsoft
Working with an established outsourcing partner that's newly investing in AI capability. Limited Strong Belitsoft
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Strong Belitsoft

Verdict: Grid Dynamics vs Belitsoft

Grid Dynamics (4.1/5) is the stronger overall choice for most AI Development projects. Nasdaq listing (GDYN) with quarterly financial disclosure.

Belitsoft (4.0/5) is worth a look if you need working with an established outsourcing partner that's newly investing in AI capability. If your situation matches that, Belitsoft is a competitive option.

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Grid Dynamics vs Belitsoft FAQ

Is Grid Dynamics better than Belitsoft?

Grid Dynamics (4.1/5) scores higher overall, but "better" depends on your use case. Grid Dynamics's strongest advantage: nasdaq listing gives enterprise procurement direct access to audited financial statements. Belitsoft's strongest advantage: two decades of outsourcing and staff augmentation experience across Poland, Latvia, and Georgia.

How do Grid Dynamics and Belitsoft differ in pricing?

Grid Dynamics uses dedicated team or retainer pricing. Belitsoft uses dedicated team or staff augmentation pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Grid Dynamics or Belitsoft?

Belitsoft 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 Belitsoft?

Grid Dynamics's primary differentiator is: nasdaq listing (GDYN) with quarterly financial disclosure. Belitsoft's primary differentiator is: twenty years of outsourcing delivery with AI added as a distinctly recent practice. They also differ in team size (4,800+ vs 250-400), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Retail & e-commerce, Financial services vs Healthcare, Fintech).

Verify all details directly with each agency before making a decision.