InData Labs vs Infosys: full comparison for 2026
Quick verdict
InData Labs (4.1/5) edges ahead of Infosys (3.9/5) overall. InData Labs is the better choice for teams needing data science depth before an AI product build. Infosys is the stronger option for global enterprises needing AI inside a full IT services contract. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Infosys: head-to-head summary
| Criterion | InData Labs | Infosys |
|---|---|---|
| Founded | 2014 | 1981 |
| HQ | Limassol, Cyprus | Bengaluru, India |
| Team size | 51-200 | 330,000+ |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Data-science-first practice rather than a generative-AI-branded service line | One of the world's largest IT services firms with a dedicated London-based consulting arm |
| Pricing model | Fixed project or dedicated team | Retainer, enterprise contracting |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, scikit-learn, TensorFlow | Python, AWS, Azure |
| Industries served | Retail & e-commerce, Gaming, Fintech, Healthcare | Financial services, Manufacturing, Retail & e-commerce, Telecom |
InData Labs vs Infosys: overview
InData Labs
InData Labs was founded in 2014 by gaming-industry veteran Marat Karpeko and is headquartered in Cyprus, with additional offices reported in Lithuania and the US. Employee figures vary from roughly 65 to 200 across different trackers, which is common for firms that mix core staff with project-based contractors. The company's practice centers on data science consulting: predictive analytics, natural language processing, computer vision, and big data analytics, positioned as a data-first alternative to firms that lead with generative AI branding.
Infosys
Infosys was founded in 1981 and is headquartered in Bengaluru, India, employing approximately 330,429 people worldwide as of March 2026. The company delivers a comprehensive suite of enterprise AI development services alongside automation, cybersecurity, and advanced data analytics, and its wholly-owned subsidiary Infosys Consulting, founded in 2004 and headquartered in London, adds a dedicated strategy and consulting layer on top. At this scale, AI development is one thread inside one of the world's largest IT services organizations rather than a boutique specialty.
Services and capabilities: InData Labs vs Infosys
| Capability | InData Labs | Infosys |
|---|---|---|
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| AI consulting | ✗ | ✓ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: InData Labs vs Infosys
| Framework / platform | InData Labs | Infosys |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | N/A | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | ✓ |
Pricing comparison: InData Labs vs Infosys
| Criterion | InData Labs | Infosys |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Dedicated team | Retainer, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs Infosys
| Dimension | InData Labs | Infosys |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & e-commerce, Gaming, Fintech | Financial services, Manufacturing, Retail & e-commerce |
| Best use cases | Building predictive models from an existing data warehouse or event stream., Adding computer vision to a product that already generates image or video data. | Running an AI initiative as part of a much larger enterprise IT services contract., Needing a globally recognized vendor for board-level procurement approval. |
| Typical project type | Fixed project | Retainer |
InData Labs vs Infosys: pros and cons
| InData Labs | |
|---|---|
| + | Founder's gaming-industry background brings real-time data experience to computer vision work. |
| + | EU-based headquarters (Cyprus) can simplify GDPR-aligned data handling for European clients. |
| + | Predictive analytics and NLP depth predate the generative AI hype cycle. |
| + | Decade-plus track record in a narrower, more defensible specialty than broad AI consulting. |
| - | Reported team size varies close to 3x across public sources |
| - | Less public-facing generative AI and LLM case work than firms built around that specifically |
| Infosys | |
|---|---|
| + | Massive global scale (330,000-plus employees) supports the largest enterprise AI programs. |
| + | Dedicated Infosys Consulting subsidiary adds a strategy layer alongside technical delivery. |
| + | Four decades of operating history and deep enterprise procurement relationships. |
| + | Broad cloud and enterprise software partnerships reduce platform risk. |
| - | AI is one part of an enormous general IT services business, not a specialized focus |
| - | Scale typically means slower engagement setup than smaller, more agile firms |
Who should choose InData Labs?
A typical fit: building predictive models from an existing data warehouse or event stream.
Data-science-first practice rather than a generative-AI-branded service line. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Gaming, Fintech, Healthcare.
Who should choose Infosys?
A typical fit: running an AI initiative as part of a much larger enterprise IT services contract.
One of the world's largest IT services firms with a dedicated London-based consulting arm. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Manufacturing, Retail & e-commerce, Telecom.
Decision matrix: InData Labs vs Infosys
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | InData Labs |
| You need a large dedicated team for an ongoing programme | InData Labs |
| Your budget is at the lower end | Compare: InData Labs (Not disclosed) vs Infosys (Not disclosed) |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Infosys |
Use case fit: InData Labs vs Infosys
| Use case | InData Labs fit | Infosys fit | Winner |
|---|---|---|---|
| Building predictive models from an existing data warehouse or event stream. | Strong | Limited | InData Labs |
| Adding computer vision to a product that already generates image or video data. | Strong | Limited | InData Labs |
| Running an AI initiative as part of a much larger enterprise IT services contract. | Strong | Strong | Both equally |
| Needing a globally recognized vendor for board-level procurement approval. | Limited | Strong | Infosys |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs Infosys
InData Labs (4.1/5) is the stronger overall choice for most AI Development projects. Data-science-first practice rather than a generative-AI-branded service line.
Infosys (3.9/5) is worth a look if you need needing a globally recognized vendor for board-level procurement approval. If your situation matches that, Infosys is a competitive option.
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InData Labs vs Infosys FAQ
Is InData Labs better than Infosys?
InData Labs (4.1/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: Founder's gaming-industry background brings real-time data experience to computer vision work. Infosys's strongest advantage: massive global scale (330,000-plus employees) supports the largest enterprise AI programs.
How do InData Labs and Infosys differ in pricing?
InData Labs uses fixed project or dedicated team pricing. Infosys uses retainer, enterprise contracting pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: InData Labs or Infosys?
Infosys 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 Infosys?
InData Labs's primary differentiator is: data-science-first practice rather than a generative-AI-branded service line. Infosys's primary differentiator is: one of the world's largest IT services firms with a dedicated London-based consulting arm. They also differ in team size (51-200 vs 330,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Retail & e-commerce, Gaming vs Financial services, Manufacturing).
Verify all details directly with each company before making a decision.