Grid Dynamics vs SoluLab: full comparison for 2026
Last updated: July 2026
Quick verdict
Grid Dynamics (4.4/5) edges ahead of SoluLab (4.1/5) overall. Grid Dynamics is the better choice for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs.. SoluLab is the stronger option for companies that want AI development from a vendor also fluent in blockchain/Web3 integration.. The right choice depends on your project size, budget, and required tech stack.
Grid Dynamics vs SoluLab: head-to-head summary
| Criterion | Grid Dynamics | SoluLab |
|---|---|---|
| Founded | 2006 | 2014 |
| HQ | San Ramon, California, United States | Woodland Hills, California, United States |
| Team size | 4,500+ | 246–250 |
| Rating | 4.4 / 5 | 4.1 / 5 |
| Best for | Fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs. | Companies that want AI development from a vendor also fluent in blockchain/Web3 integration. |
| Pricing model | Time & materials, managed engagement | Project-based, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | AWS SageMaker, Kubernetes, Apache Spark | OpenAI API, LangChain, Python |
| Industries served | Retail & E-commerce, Manufacturing, Insurance, Media & Entertainment, Telecom | Media & Entertainment, Automotive, Education, FinTech |
Grid Dynamics vs SoluLab: overview
Grid Dynamics
Grid Dynamics Holdings, Inc. (Nasdaq: GDYN) was founded in 2006 in Silicon Valley by Leonard Livschitz and is headquartered in San Ramon, California, with roughly 4,500–5,000 technical professionals across 19 countries. The company delivers enterprise AI/ML and data platform engineering alongside cloud-native engineering, serving Fortune 1000 clients in retail, manufacturing, insurance, wealth management, and life sciences. As a publicly traded company, Grid Dynamics carries a higher compliance and financial-transparency bar than most privately held firms in this list, at the cost of boutique-level personalization.
SoluLab
SoluLab was founded in 2014–2015 by Chintan Thakkar and Rajat Lala and is headquartered in Woodland Hills, California, with a team of roughly 246–250 engineers, data scientists, and AI specialists. The firm positions itself as an 'AI-native, Blockchain, and Web3' development company and reports having delivered 1,500+ projects across 15+ countries for clients including The Walt Disney Company, Mercedes-Benz, and the University of Cambridge (per company website; independently unverifiable at this scale). Its dual focus on AI and blockchain/Web3 makes it broader than a pure ML specialist.
Services and capabilities: Grid Dynamics vs SoluLab
| Capability | Grid Dynamics | SoluLab |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✓ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: Grid Dynamics vs SoluLab
| Framework / platform | Grid Dynamics | SoluLab |
|---|---|---|
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Grid Dynamics vs SoluLab
| Criterion | Grid Dynamics | SoluLab |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated team, Managed engagement, Staff augmentation | Project-based, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Grid Dynamics vs SoluLab
| Dimension | Grid Dynamics | SoluLab |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & E-commerce, Manufacturing, Insurance | Media & Entertainment, Automotive, Education |
| Best use cases | Fortune 1000 retailer needs an enterprise-scale ML/data platform overhaul with public-company accountability., Insurance or wealth management firm needs a vendor with SEC-level financial transparency for procurement due diligence. | Company building an AI product with a blockchain or Web3 component needs a single integrated vendor., Enterprise wants a vendor with named brand-name reference clients for procurement comfort. |
| Typical project type | Dedicated team | Project-based |
Grid Dynamics vs SoluLab: pros and cons
| Grid Dynamics | |
|---|---|
| + | Publicly traded (Nasdaq: GDYN) status means audited financials and SEC disclosure are available to prospective clients — a rare transparency level in this list. |
| + | ~4,500 technical professionals across 19 countries gives it the delivery capacity for large, multi-workstream Fortune 1000 programs. |
| + | 18 years of enterprise engineering experience since 2006, well before the current AI hiring wave. |
| + | Combines cloud-native and AI/ML engineering under one roof, reducing multi-vendor coordination for large programs. |
| - | At ~4,500 employees, engagements are structured around managed delivery teams rather than boutique-style founder involvement. |
| - | Public-company overhead and scale generally mean higher minimum program sizes than smaller specialist firms. |
| SoluLab | |
|---|---|
| + | Named enterprise clients (The Walt Disney Company, Mercedes-Benz, University of Cambridge) offer verifiable reference points, though the specific scope of each engagement is unconfirmed. |
| + | 246–250 team size supports mid-to-large engagements without enterprise-firm overhead. |
| + | Combined AI and blockchain/Web3 capability is useful for clients building tokenized or decentralized AI products. |
| + | 10 years of company history (since 2014–2015) under continuous founder leadership. |
| - | 1,500+ projects claim across 15+ countries is difficult to independently verify at face value. |
| - | Blockchain/Web3 focus alongside AI means clients purely interested in ML may be paying for adjacent expertise they don't need. |
Who should choose Grid Dynamics?
Grid Dynamics is the right choice for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs..
Nasdaq-listed enterprise AI engineering firm with public financial reporting and Fortune 1000 client base.. Minimum engagement starts at Not published. Works best with clients in Retail & E-commerce, Manufacturing, Insurance, Media & Entertainment, Telecom.
Who should choose SoluLab?
SoluLab is the right choice for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
Combines AI-native development with blockchain/Web3 expertise under one delivery team.. Minimum engagement starts at Not published. Works best with clients in Media & Entertainment, Automotive, Education, FinTech.
Decision matrix: Grid Dynamics vs SoluLab
| 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 published) vs SoluLab (Not published) |
| You need specialist depth in a specific vertical | Grid Dynamics |
| You need production MLOps support after model launch | Grid Dynamics |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: Grid Dynamics vs SoluLab
| Use case | Grid Dynamics fit | SoluLab fit | Winner |
|---|---|---|---|
| Fortune 1000 retailer needs an enterprise-scale ML/data platform overhaul with public-company accountability. | Strong | Limited | Grid Dynamics |
| Insurance or wealth management firm needs a vendor with SEC-level financial transparency for procurement due diligence. | Strong | Limited | Grid Dynamics |
| Company building an AI product with a blockchain or Web3 component needs a single integrated vendor. | Strong | Strong | Both equally |
| Enterprise wants a vendor with named brand-name reference clients for procurement comfort. | Strong | Strong | Both equally |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: Grid Dynamics vs SoluLab
Grid Dynamics (4.4/5) is the stronger overall choice for most Machine Learning Development projects. Nasdaq-listed enterprise AI engineering firm with public financial reporting and Fortune 1000 client base.. It is best for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs..
SoluLab (4.1/5) is the better choice when companies that want AI development from a vendor also fluent in blockchain/Web3 integration.. If your situation matches those criteria, SoluLab is a competitive option.
Related comparisons
Grid Dynamics vs SoluLab FAQ
Is Grid Dynamics better than SoluLab?
Grid Dynamics (4.4/5) scores higher overall, but "better" depends on your use case. Grid Dynamics is better for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs.. SoluLab is better for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
How do Grid Dynamics and SoluLab differ in pricing?
Grid Dynamics uses time & materials, managed engagement pricing with a minimum engagement of Not published. SoluLab uses project-based, dedicated team 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 SoluLab?
SoluLab 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 Grid Dynamics and SoluLab?
Grid Dynamics's primary differentiator is: nasdaq-listed enterprise ai engineering firm with public financial reporting and fortune 1000 client base.. SoluLab's primary differentiator is: combines ai-native development with blockchain/web3 expertise under one delivery team.. They also differ in team size (4,500+ vs 246–250), minimum engagement (Not published vs Not published), and primary industries served (Retail & E-commerce, Manufacturing vs Media & Entertainment, Automotive).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.