InData Labs vs Markovate: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.5/5) edges ahead of Markovate (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.. Markovate is the stronger option for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM).. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Markovate: head-to-head summary
| Criterion | InData Labs | Markovate |
|---|---|---|
| Founded | 2014 | 2015 |
| HQ | Limassol, Cyprus | San Francisco, California, United States |
| Team size | 50–100 | 50–100 |
| 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 wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM). |
| Pricing model | Project-based, dedicated team | Project-based, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | LangChain, OpenAI API, Python |
| Industries served | FinTech, Healthcare, Retail & E-commerce, Logistics & Supply Chain | Healthcare, Retail & E-commerce, FinTech, Travel & Hospitality |
InData Labs vs Markovate: 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.
Markovate
Markovate was founded in 2015 and is led by CEO Rajeev Sharma, an AI veteran with 18+ years of experience who previously led AI initiatives at AT&T and IBM. Headquartered with a San Francisco address (some sources cite Toronto as an operating base), the company has grown to roughly 51 employees, including 50+ engineers described as 'certified AI engineers' (per company website), delivering custom AI agents, chatbot development, and cloud services for healthcare, retail, fintech, SaaS, and travel clients. Its small team size makes it a boutique play best suited to scoped generative AI or agent projects rather than large-scale programs.
Services and capabilities: InData Labs vs Markovate
| Capability | InData Labs | Markovate |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✓ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: InData Labs vs Markovate
| Framework / platform | InData Labs | Markovate |
|---|---|---|
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | N/A | ✓ |
| LangChain | N/A | ✓ |
| Hugging Face | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: InData Labs vs Markovate
| Criterion | InData Labs | Markovate |
|---|---|---|
| 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 Markovate
| Dimension | InData Labs | Markovate |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, Retail & E-commerce | Healthcare, Retail & E-commerce, 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. | Company wants an AI agent or chatbot built by a team led by a former enterprise AI executive., Healthcare or fintech startup needs a scoped generative AI project from a small, focused vendor. |
| Typical project type | Project-based | Project-based |
InData Labs vs Markovate: 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. |
| Markovate | |
|---|---|
| + | CEO's 18+ years leading AI initiatives at AT&T and IBM brings genuine enterprise AI leadership experience to client engagements. |
| + | Focused service scope (AI agents, chatbots, generative AI) rather than a broad, diluted general-consulting offering. |
| + | Serves a wide industry spread (healthcare to travel) despite small team size, suggesting adaptable delivery patterns. |
| - | At roughly 51 employees, capacity for multiple concurrent large engagements is limited. |
| - | HQ location is inconsistently reported (San Francisco vs. Toronto across sources) — confirm the contracting entity directly. |
| - | "50+ certified AI engineers" claim on a 51-person total headcount is a company claim worth verifying during vendor due diligence. |
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 Markovate?
Markovate is the right choice for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM)..
CEO brings direct enterprise AI leadership experience (AT&T, IBM) rather than a purely technical or agency background.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Retail & E-commerce, FinTech, Travel & Hospitality.
Decision matrix: InData Labs vs Markovate
| 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 Markovate (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 Markovate
| Use case | InData Labs fit | Markovate fit | Winner |
|---|---|---|---|
| FinTech company needs predictive analytics built by a team that has done nothing but AI/data science since 2014. | Strong | Strong | Both equally |
| Healthcare startup needs a computer vision model with a small, senior delivery team. | Strong | Strong | Both equally |
| Company wants an AI agent or chatbot built by a team led by a former enterprise AI executive. | Strong | Strong | Both equally |
| Healthcare or fintech startup needs a scoped generative AI project from a small, focused vendor. | Strong | Strong | Both equally |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: InData Labs vs Markovate
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..
Markovate (4.1/5) is the better choice when companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM).. If your situation matches those criteria, Markovate is a competitive option.
Related comparisons
InData Labs vs Markovate FAQ
Is InData Labs better than Markovate?
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.. Markovate is better for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM)..
How do InData Labs and Markovate differ in pricing?
InData Labs uses project-based, dedicated team pricing with a minimum engagement of Not published. Markovate 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 Markovate?
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 Markovate?
InData Labs's primary differentiator is: ten-plus years as a pure-play ai/data-science firm with no general software-development sideline.. Markovate's primary differentiator is: ceo brings direct enterprise ai leadership experience (at&t, ibm) rather than a purely technical or agency background.. They also differ in team size (50–100 vs 50–100), minimum engagement (Not published vs Not published), and primary industries served (FinTech, Healthcare vs Healthcare, Retail & E-commerce).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.