InData Labs vs Space-O Technologies: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.5/5) edges ahead of Space-O Technologies (4.0/5) overall. InData Labs is the better choice for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead.. 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.
InData Labs vs Space-O Technologies: head-to-head summary
| Criterion | InData Labs | Space-O Technologies |
|---|---|---|
| Founded | 2014 | 2010 |
| HQ | Limassol, Cyprus | Ahmedabad, India |
| Team size | 50–100 | 140+ |
| Rating | 4.5 / 5 | 4.0 / 5 |
| Best for | FinTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead. | 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 | Python, TensorFlow, PyTorch | TensorFlow, Keras, OpenAI API |
| Industries served | FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain | Healthcare, EdTech, Retail & E-commerce, Travel & Hospitality |
InData Labs vs Space-O Technologies: 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.
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: InData Labs vs Space-O Technologies
| Capability | InData Labs | Space-O Technologies |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: InData Labs vs Space-O Technologies
| Framework / platform | InData Labs | Space-O Technologies |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | N/A |
| 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 Space-O Technologies
| Criterion | InData Labs | 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: InData Labs vs Space-O Technologies
| Dimension | InData Labs | Space-O Technologies |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, Retail & E-commerce | Healthcare, EdTech, Retail & E-commerce |
| 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 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 |
InData Labs vs Space-O Technologies: 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. |
| 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 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 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: InData Labs 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 | InData Labs |
| Your budget is at the lower end | Compare: InData Labs (Not published) vs Space-O Technologies (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 Space-O Technologies
| Use case | InData Labs fit | Space-O Technologies 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 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: InData Labs vs Space-O Technologies
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..
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
InData Labs vs Space-O Technologies FAQ
Is InData Labs better than Space-O Technologies?
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.. 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 InData Labs and Space-O Technologies differ in pricing?
InData Labs 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: InData Labs or Space-O Technologies?
InData Labs 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 Space-O Technologies?
InData Labs's primary differentiator is: ten-plus years as a pure-play ai/data-science firm with no general software-development sideline.. 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 (50–100 vs 140+), minimum engagement (Not published vs Not published), and primary industries served (FinTech, Healthcare vs Healthcare, EdTech).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.