InData Labs vs Intellias: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.5/5) edges ahead of Intellias (3.7/5) overall. InData Labs is the better choice for finTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead.. Intellias is the stronger option for automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage.. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Intellias: head-to-head summary
| Criterion | InData Labs | Intellias |
|---|---|---|
| Founded | 2014 | 2002 |
| HQ | Limassol, Cyprus | Sliema, Malta |
| Team size | 50–100 | 2,961 |
| Rating | 4.5 / 5 | 3.7 / 5 |
| Best for | FinTech, healthcare, and SaaS companies that want a decade-old AI specialist without enterprise-scale overhead. | Automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage. |
| Pricing model | Project-based, dedicated team | Time & materials, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, AWS, Azure |
| Industries served | FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain | Automotive, Manufacturing, FinTech, Retail & E-commerce |
InData Labs vs Intellias: 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.
Intellias
Intellias was founded in 2002 in Lviv, Ukraine by Michael Puzrakov and Vitaly Sedler and now lists its headquarters in Sliema, Malta, with a workforce exceeding 2,961 employees (some sources cite 3,000+). The company specializes in IoT, artificial intelligence, machine learning, big data, cloud computing, data science, and DevOps, and has been listed among top service providers by Clutch, IAOP, and the GSA UK Awards. Its automotive and mobility-sector heritage gives it particular depth in embedded/IoT-adjacent ML applications relative to more general-purpose AI consultancies.
Services and capabilities: InData Labs vs Intellias
| Capability | InData Labs | Intellias |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✗ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: InData Labs vs Intellias
| Framework / platform | InData Labs | Intellias |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: InData Labs vs Intellias
| Criterion | InData Labs | Intellias |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team | Dedicated team, Time & materials, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs Intellias
| Dimension | InData Labs | Intellias |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, Retail & E-commerce | Automotive, Manufacturing, FinTech |
| 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. | Automotive or mobility company needs ML development from a firm with genuine embedded-systems and IoT heritage., Enterprise wants a vendor recognized by three independent bodies (Clutch, IAOP, GSA UK) rather than one. |
| Typical project type | Project-based | Dedicated team |
InData Labs vs Intellias: 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. |
| Intellias | |
|---|---|
| + | 22+ years of operating history (since 2002) with founders still traceable to the company's Lviv origins. |
| + | 2,961-person workforce provides strong delivery capacity for large, multi-workstream enterprise programs. |
| + | Recognized among top service providers by Clutch, IAOP, and the GSA UK Awards — three independent bodies rather than one. |
| + | Automotive and IoT sector depth differentiates it from generalist ML consultancies for embedded/connected-device use cases. |
| - | Legal headquarters in Sliema, Malta while founding and significant delivery capacity remains tied to Lviv, Ukraine — confirm contracting jurisdiction. |
| - | At nearly 3,000 employees, AI/ML is one of several core specializations (IoT, big data, cloud, DevOps) rather than a standalone focus. |
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 Intellias?
Intellias is the right choice for automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage..
Strong automotive/mobility and IoT sector heritage, giving it differentiated depth in embedded and connected-device ML use cases.. Minimum engagement starts at Not published. Works best with clients in Automotive, Manufacturing, FinTech, Retail & E-commerce.
Decision matrix: InData Labs vs Intellias
| 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 Intellias (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 Intellias
| Use case | InData Labs fit | Intellias 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 |
| Automotive or mobility company needs ML development from a firm with genuine embedded-systems and IoT heritage. | Limited | Strong | Intellias |
| Enterprise wants a vendor recognized by three independent bodies (Clutch, IAOP, GSA UK) rather than one. | Limited | Strong | Intellias |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: InData Labs vs Intellias
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..
Intellias (3.7/5) is the better choice when automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage.. If your situation matches those criteria, Intellias is a competitive option.
Related comparisons
InData Labs vs Intellias FAQ
Is InData Labs better than Intellias?
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.. Intellias is better for automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage..
How do InData Labs and Intellias differ in pricing?
InData Labs uses project-based, dedicated team pricing with a minimum engagement of Not published. Intellias uses time & materials, 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 Intellias?
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 Intellias?
InData Labs's primary differentiator is: ten-plus years as a pure-play ai/data-science firm with no general software-development sideline.. Intellias's primary differentiator is: strong automotive/mobility and iot sector heritage, giving it differentiated depth in embedded and connected-device ml use cases.. They also differ in team size (50–100 vs 2,961), minimum engagement (Not published vs Not published), and primary industries served (FinTech, Healthcare vs Automotive, Manufacturing).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.