InData Labs vs SoluLab: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.5/5) edges ahead of SoluLab (4.1/5) overall. InData Labs is the better choice for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead.. 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.
InData Labs vs SoluLab: head-to-head summary
| Criterion | InData Labs | SoluLab |
|---|---|---|
| Founded | 2014 | 2014 |
| HQ | Limassol, Cyprus | Woodland Hills, California, United States |
| Team size | 50–100 | 246–250 |
| Rating | 4.5 / 5 | 4.1 / 5 |
| Best for | FinTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead. | 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 | Python, TensorFlow, PyTorch | OpenAI API, LangChain, Python |
| Industries served | FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain | Media & Entertainment, Automotive, Education, FinTech |
InData Labs vs SoluLab: overview
InData Labs
InData Labs was founded in 2014 by Marat Karpeko and is headquartered in Limassol, Cyprus, with additional offices in Lithuania and the United States. The company has stayed a pure-play AI/data-science consultancy for over a decade, building production ML systems for fintech, healthcare, SaaS, retail, and logistics clients, and is listed in Clutch's Top 10 AI Software Companies leaders matrix. At roughly 80 professionals, it is one of the smaller specialist firms in this list, trading scale for narrower focus.
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: InData Labs vs SoluLab
| Capability | InData Labs | SoluLab |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: InData Labs vs SoluLab
| Framework / platform | InData Labs | 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 |
| Kubernetes | N/A | N/A |
Pricing comparison: InData Labs vs SoluLab
| Criterion | InData Labs | SoluLab |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team | Project-based, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs SoluLab
| Dimension | InData Labs | SoluLab |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, Retail & E-commerce | Media & Entertainment, Automotive, Education |
| Best use cases | FinTech company needs predictive analytics built by a team that has done nothing but AI/data science since 2014., Healthcare startup needs a computer vision model with a small, senior delivery team. | 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 |
InData Labs vs SoluLab: pros and cons
| InData Labs | |
|---|---|
| + | Has operated as a dedicated AI/data science firm since 2014 with no pivot to general software outsourcing. |
| + | Ranked in Clutch's Top 10 AI Software Companies leaders matrix. |
| + | Covers the full pipeline from data engineering through generative AI and computer vision, avoiding narrow single-service lock-in. |
| + | Smaller team size (~80) generally means less account-management overhead between client and engineers. |
| - | At roughly 80 people, InData Labs cannot staff large multi-workstream enterprise programs the way a 2,000+ person firm can. |
| - | Limassol, Cyprus HQ has a thinner regional case-study base in North America compared to US-headquartered peers. |
| 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 InData Labs?
InData Labs is the right choice for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead..
Ten-plus years as a pure-play AI/data-science firm with no general software-development sideline.. Minimum engagement starts at Not published. Works best with clients in FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain.
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: InData Labs 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 | InData Labs |
| Your budget is at the lower end | Compare: InData Labs (Not published) vs SoluLab (Not published) |
| You need specialist depth in a specific vertical | InData Labs |
| You need production MLOps support after model launch | Both offer MLOps support |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: InData Labs vs SoluLab
| Use case | InData Labs fit | SoluLab fit | Winner |
|---|---|---|---|
| FinTech company needs predictive analytics built by a team that has done nothing but AI/data science since 2014. | Strong | Limited | InData Labs |
| Healthcare startup needs a computer vision model with a small, senior delivery team. | Strong | Limited | InData Labs |
| 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. | Limited | Strong | SoluLab |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: InData Labs vs SoluLab
InData Labs (4.5/5) is the stronger overall choice for most Machine Learning Development projects. Ten-plus years as a pure-play AI/data-science firm with no general software-development sideline.. It is best for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead..
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
InData Labs vs SoluLab FAQ
Is InData Labs better than SoluLab?
InData Labs (4.5/5) scores higher overall, but "better" depends on your use case. InData Labs is better for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead.. SoluLab is better for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
How do InData Labs and SoluLab differ in pricing?
InData Labs 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: InData Labs 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 InData Labs and SoluLab?
InData Labs's primary differentiator is: ten-plus years as a pure-play ai/data-science firm with no general software-development sideline.. SoluLab's primary differentiator is: combines ai-native development with blockchain/web3 expertise under one delivery team.. They also differ in team size (50–100 vs 246–250), minimum engagement (Not published vs Not published), and primary industries served (FinTech, Healthcare vs Media & Entertainment, Automotive).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.