SoluLab vs Space-O Technologies: full comparison for 2026
Last updated: July 2026
Quick verdict
SoluLab (4.1/5) edges ahead of Space-O Technologies (4.0/5) overall. SoluLab is the better choice for companies that want AI development from a vendor also fluent in blockchain/Web3 integration.. Space-O Technologies is the stronger option for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement.. The right choice depends on your project size, budget, and required tech stack.
SoluLab vs Space-O Technologies: head-to-head summary
| Criterion | SoluLab | Space-O Technologies |
|---|---|---|
| Founded | 2014 | 2010 |
| HQ | Woodland Hills, California, United States | Ahmedabad, India |
| Team size | 246–250 | 140+ |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Best for | Companies that want AI development from a vendor also fluent in blockchain/Web3 integration. | Companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement. |
| Pricing model | Project-based, dedicated team | Project-based, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | OpenAI API, LangChain, Python | TensorFlow, Keras, OpenAI API |
| Industries served | Media & Entertainment, Automotive, Education, FinTech | Healthcare, EdTech, Retail & E-commerce, Travel & Hospitality |
SoluLab vs Space-O Technologies: overview
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.
Space-O Technologies
Space-O Technologies was founded in 2010 by Rakeshkumar Patel and Atit Tusharbhai Purani, growing to roughly 140 full-stack engineers and AI specialists with offices in the US, Canada, and India. The company built its reputation on mobile app development (including early on-demand apps and EdTech products) before extending into machine learning on both neural and non-neural networks, working with frameworks including Keras, Caffe, and TensorFlow, plus more recent integration of OpenAI's GPT, Whisper, and LangChain. Its origin as a mobile-app shop means ML is a newer, added capability rather than the company's founding focus.
Services and capabilities: SoluLab vs Space-O Technologies
| Capability | SoluLab | Space-O Technologies |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: SoluLab vs Space-O Technologies
| Framework / platform | SoluLab | Space-O Technologies |
|---|---|---|
| TensorFlow | N/A | ✓ |
| PyTorch | N/A | N/A |
| AWS | ✓ | N/A |
| 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: SoluLab vs Space-O Technologies
| Criterion | SoluLab | Space-O Technologies |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team | Project-based, Dedicated team, Fixed project |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: SoluLab vs Space-O Technologies
| Dimension | SoluLab | Space-O Technologies |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Media & Entertainment, Automotive, Education | Healthcare, EdTech, Retail & E-commerce |
| Best use cases | 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. | Company needs an ML feature (recommendation, prediction, chatbot) built directly into a new or existing mobile app., EdTech or travel company wants a single vendor for both application development and embedded AI features. |
| Typical project type | Project-based | Project-based |
SoluLab vs Space-O Technologies: pros and cons
| 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. |
| Space-O Technologies | |
|---|---|
| + | 15 years of product-delivery history (since 2010), with a track record that includes early on-demand and EdTech app development. |
| + | 300+ delivered software solutions and 1,200+ clients gives it a broad delivery pattern library. |
| + | Integrates modern generative AI tooling (GPT, Whisper, LangChain) alongside classical ML frameworks (Keras, Caffe, TensorFlow). |
| + | Offices across US, Canada, and India provide time-zone coverage for North American clients. |
| - | Company's core identity and longest track record is in mobile app development, not ML — AI/ML is a newer, extended service line. |
| - | 140-person team spread across app development, AI development, and other services means ML-specific bench depth is smaller than the total headcount suggests. |
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.
Who should choose Space-O Technologies?
Space-O Technologies is the right choice for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement..
15 years of mobile/software product delivery experience (since 2010) with ML added as a production-application capability.. Minimum engagement starts at Not published. Works best with clients in Healthcare, EdTech, Retail & E-commerce, Travel & Hospitality.
Decision matrix: SoluLab vs Space-O Technologies
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Space-O Technologies |
| You need a large dedicated team for an ongoing programme | SoluLab |
| Your budget is at the lower end | Compare: SoluLab (Not published) vs Space-O Technologies (Not published) |
| You need specialist depth in a specific vertical | SoluLab |
| 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: SoluLab vs Space-O Technologies
| Use case | SoluLab fit | Space-O Technologies fit | Winner |
|---|---|---|---|
| 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 | Limited | SoluLab |
| Company needs an ML feature (recommendation, prediction, chatbot) built directly into a new or existing mobile app. | Strong | Strong | Both equally |
| EdTech or travel company wants a single vendor for both application development and embedded AI features. | Limited | Strong | Space-O Technologies |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: SoluLab vs Space-O Technologies
SoluLab (4.1/5) is the stronger overall choice for most Machine Learning Development projects. Combines AI-native development with blockchain/Web3 expertise under one delivery team.. It is best for companies that want AI development from a vendor also fluent in blockchain/Web3 integration..
Space-O Technologies (4.0/5) is the better choice when companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement.. If your situation matches those criteria, Space-O Technologies is a competitive option.
Related comparisons
SoluLab vs Space-O Technologies FAQ
Is SoluLab better than Space-O Technologies?
SoluLab (4.1/5) scores higher overall, but "better" depends on your use case. SoluLab is better for companies that want AI development from a vendor also fluent in blockchain/Web3 integration.. Space-O Technologies is better for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement..
How do SoluLab and Space-O Technologies differ in pricing?
SoluLab uses project-based, dedicated team pricing with a minimum engagement of Not published. Space-O Technologies 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: SoluLab or Space-O Technologies?
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 SoluLab and Space-O Technologies?
SoluLab's primary differentiator is: combines ai-native development with blockchain/web3 expertise under one delivery team.. Space-O Technologies's primary differentiator is: 15 years of mobile/software product delivery experience (since 2010) with ml added as a production-application capability.. They also differ in team size (246–250 vs 140+), minimum engagement (Not published vs Not published), and primary industries served (Media & Entertainment, Automotive vs Healthcare, EdTech).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.