Master of Code Global vs SoluLab: full comparison for 2026
Last updated: July 2026
Quick verdict
Master of Code Global (4.1/5) edges ahead of SoluLab (4.1/5) overall. Master of Code Global is the better choice for enterprise brands that need chat or voice AI experiences built by a firm with two decades of conversational-AI focus.. 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.
Master of Code Global vs SoluLab: head-to-head summary
| Criterion | Master of Code Global | SoluLab |
|---|---|---|
| Founded | 2004 | 2014 |
| HQ | Redwood City, California, United States | Woodland Hills, California, United States |
| Team size | 200–250 | 246–250 |
| Rating | 4.1 / 5 | 4.1 / 5 |
| Best for | Enterprise brands that need chat or voice AI experiences built by a firm with two decades of conversational-AI focus. | Companies that want AI development from a vendor also fluent in blockchain/Web3 integration. |
| Pricing model | Project-based, dedicated team | Project-based, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | LangChain, OpenAI API, Python | OpenAI API, LangChain, Python |
| Industries served | Retail & E-commerce, Telecom, FinTech, Media & Entertainment | Media & Entertainment, Automotive, Education, FinTech |
Master of Code Global vs SoluLab: overview
Master of Code Global
Master of Code Global was founded in 2004 and has grown under CEO Dmitry Gritsenko to roughly 200–250 professionals, with headquarters listed in both Winnipeg, Canada and Redwood City, California. The company specializes in enterprise-grade chat and voice AI solutions, reporting more than 1,000 completed projects for clients including T-Mobile, Burberry, Tom Ford, and Dr. Oetker (per company website; independently unverifiable claim of '1 billion+ users'). Its focus on AI development, AI agents, AI consulting, and generative AI (a combined 85% of stated service mix) makes it one of the more conversational-AI-concentrated firms in this list.
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: Master of Code Global vs SoluLab
| Capability | Master of Code Global | SoluLab |
|---|---|---|
| Custom ML Models | ✗ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✓ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✓ | ✗ |
Tech stack comparison: Master of Code Global vs SoluLab
| Framework / platform | Master of Code Global | SoluLab |
|---|---|---|
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Master of Code Global vs SoluLab
| Criterion | Master of Code Global | SoluLab |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team, Retainer | Project-based, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Master of Code Global vs SoluLab
| Dimension | Master of Code Global | SoluLab |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & E-commerce, Telecom, FinTech | Media & Entertainment, Automotive, Education |
| Best use cases | Enterprise retail or telecom brand needs a chatbot or voice AI experience built by a specialist., Company wants a vendor with named, verifiable enterprise client references for procurement. | 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 | Project-based | Project-based |
Master of Code Global vs SoluLab: pros and cons
| Master of Code Global | |
|---|---|
| + | Named enterprise clients (T-Mobile, Burberry, Tom Ford, Dr. Oetker) provide verifiable, non-anonymized proof points. |
| + | 20 years of company history (since 2004), with a specific and consistent focus on conversational AI rather than pivoting service lines yearly. |
| + | 1,000+ completed projects gives the firm a large delivery pattern library for chat/voice use cases. |
| + | 200–250 team size is large enough for enterprise brand engagements but still small enough for direct account access. |
| - | "1 billion+ users" figure is a company claim without independent verification. |
| - | Conversational AI concentration (chat/voice) means less depth in computer vision or predictive analytics relative to broader ML 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 Master of Code Global?
Master of Code Global is the right choice for enterprise brands that need chat or voice AI experiences built by a firm with two decades of conversational-AI focus..
20-year specialization in enterprise chat and voice AI, with named enterprise clients like T-Mobile and Burberry.. Minimum engagement starts at Not published. Works best with clients in Retail & E-commerce, Telecom, FinTech, Media & Entertainment.
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: Master of Code Global 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 | Master of Code Global |
| Your budget is at the lower end | Compare: Master of Code Global (Not published) vs SoluLab (Not published) |
| You need specialist depth in a specific vertical | Master of Code Global |
| You need production MLOps support after model launch | Both offer MLOps support |
| You need consulting before committing to a build | Master of Code Global |
Use case fit: Master of Code Global vs SoluLab
| Use case | Master of Code Global fit | SoluLab fit | Winner |
|---|---|---|---|
| Enterprise retail or telecom brand needs a chatbot or voice AI experience built by a specialist. | Strong | Strong | Both equally |
| Company wants a vendor with named, verifiable enterprise client references for procurement. | Strong | Strong | Both equally |
| 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: Master of Code Global vs SoluLab
Master of Code Global (4.1/5) is the stronger overall choice for most Machine Learning Development projects. 20-year specialization in enterprise chat and voice AI, with named enterprise clients like T-Mobile and Burberry.. It is best for enterprise brands that need chat or voice AI experiences built by a firm with two decades of conversational-AI focus..
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
Master of Code Global vs SoluLab FAQ
Is Master of Code Global better than SoluLab?
Master of Code Global (4.1/5) scores higher overall, but "better" depends on your use case. Master of Code Global is better for enterprise brands that need chat or voice AI experiences built by a firm with two decades of conversational-AI focus.. SoluLab is better for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
How do Master of Code Global and SoluLab differ in pricing?
Master of Code Global uses project-based, dedicated team 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: Master of Code Global 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 Master of Code Global and SoluLab?
Master of Code Global's primary differentiator is: 20-year specialization in enterprise chat and voice ai, with named enterprise clients like t-mobile and burberry.. SoluLab's primary differentiator is: combines ai-native development with blockchain/web3 expertise under one delivery team.. They also differ in team size (200–250 vs 246–250), minimum engagement (Not published vs Not published), and primary industries served (Retail & E-commerce, Telecom vs Media & Entertainment, Automotive).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.