Capgemini Invent vs InData Labs: full comparison for 2026
Quick verdict
Capgemini Invent (4.2/5) edges ahead of InData Labs (3.9/5) overall. Capgemini Invent is the better choice for european enterprises wanting generative AI strategy from a Paris-based consultancy. InData Labs is the stronger option for teams needing data science consulting before a generative AI build. The right choice depends on your project size, budget, and required tech stack.
Capgemini Invent vs InData Labs: head-to-head summary
| Criterion | Capgemini Invent | InData Labs |
|---|---|---|
| Founded | 2018 | 2014 |
| HQ | Paris, France | Limassol, Cyprus |
| Team size | 17,000+ | 51-200 |
| Rating | 4.2 / 5 | 3.9 / 5 |
| Primary differentiator | 17,000-plus person strategy and design brand backed by the wider Capgemini Group | Data-science-first heritage predating the generative AI branding wave |
| Pricing model | Retainer, enterprise contracting | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, scikit-learn, TensorFlow |
| Industries served | Financial services, Manufacturing, Retail & e-commerce, Automotive | Retail & e-commerce, Gaming, Fintech, Healthcare |
Capgemini Invent vs InData Labs: overview
Capgemini Invent
Capgemini Invent launched in 2018 as the digital innovation, consulting, and transformation brand of the broader Capgemini Group, headquartered in Paris. Reported headcount varies between roughly 17,000 and 18,000-plus across six continents. It combines strategy consulting with data science and creative design under one brand, positioning generative AI work as part of a broader digital transformation practice rather than a standalone specialty.
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. Staff estimates swing between roughly 65 and 200 across sources. Its practice centers on data science consulting, predictive analytics, natural language processing, and computer vision, positioning it closer to a data-first consultancy than a generative-AI-branded agency chasing the current trend.
Services and capabilities: Capgemini Invent vs InData Labs
| Capability | Capgemini Invent | InData Labs |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| Machine learning | ✗ | ✓ |
| Data engineering | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Fixed-price projects | ✗ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Capgemini Invent vs InData Labs
| Framework / platform | Capgemini Invent | InData Labs |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: Capgemini Invent vs InData Labs
| Criterion | Capgemini Invent | InData Labs |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Retainer, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Capgemini Invent vs InData Labs
| Dimension | Capgemini Invent | InData Labs |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Manufacturing, Retail & e-commerce | Retail & e-commerce, Gaming, Fintech |
| Best use cases | Running a European enterprise generative AI strategy engagement with an EU-incorporated vendor., Pairing generative AI consulting with broader digital transformation and design work. | Getting a data science consulting assessment before committing to a full generative AI build., Adding computer vision strategy to a product that already produces image or video data. |
| Typical project type | Retainer | Fixed project |
Capgemini Invent vs InData Labs: pros and cons
| Capgemini Invent | |
|---|---|
| + | Paris headquarters gives EU-based clients a genuine EU legal entity for generative AI consulting work. |
| + | 17,000-plus staff across six continents supports large, distributed enterprise programs. |
| + | Backed by the wider Capgemini Group's technology delivery capacity. |
| + | Combines strategy consulting with data science and design under one brand. |
| - | Generative AI work sits inside a broader digital transformation brand rather than as a standalone specialty |
| - | Reported headcount varies notably across public sources, from roughly 17,000 to over 18,000 |
| InData Labs | |
|---|---|
| + | Founder's gaming background brings real-time data processing experience to computer vision work. |
| + | Cyprus headquarters (EU-based) can simplify GDPR-aligned data handling for European clients. |
| + | Predictive analytics and NLP expertise predates the current generative AI wave. |
| + | More than a decade of track record in a narrower, more defensible specialty. |
| - | Reported team size varies close to 3x across public sources |
| - | Less generative AI and LLM-specific public case work than firms built specifically around that |
Who should choose Capgemini Invent?
A typical fit: running a European enterprise generative AI strategy engagement with an EU-incorporated vendor.
17,000-plus person strategy and design brand backed by the wider Capgemini Group. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Manufacturing, Retail & e-commerce, Automotive.
Who should choose InData Labs?
A typical fit: getting a data science consulting assessment before committing to a full generative AI build.
Data-science-first heritage predating the generative AI branding wave. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Gaming, Fintech, Healthcare.
Decision matrix: Capgemini Invent vs InData Labs
| 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 | Capgemini Invent |
| Your budget is at the lower end | Compare: Capgemini Invent (Not disclosed) vs InData Labs (Not disclosed) |
| You need specialist depth in a specific vertical | Capgemini Invent |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Capgemini Invent |
Use case fit: Capgemini Invent vs InData Labs
| Use case | Capgemini Invent fit | InData Labs fit | Winner |
|---|---|---|---|
| Running a European enterprise generative AI strategy engagement with an EU-incorporated vendor. | Strong | Strong | Both equally |
| Pairing generative AI consulting with broader digital transformation and design work. | Strong | Limited | Capgemini Invent |
| Getting a data science consulting assessment before committing to a full generative AI build. | Limited | Strong | InData Labs |
| Adding computer vision strategy to a product that already produces image or video data. | Limited | Strong | InData Labs |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: Capgemini Invent vs InData Labs
Capgemini Invent (4.2/5) is the stronger overall choice for most Generative AI Consulting projects. 17,000-plus person strategy and design brand backed by the wider Capgemini Group.
InData Labs (3.9/5) is worth a look if you need adding computer vision strategy to a product that already produces image or video data. If your situation matches that, InData Labs is a competitive option.
Related comparisons
Capgemini Invent vs InData Labs FAQ
Is Capgemini Invent better than InData Labs?
Capgemini Invent (4.2/5) scores higher overall, but "better" depends on your use case. Capgemini Invent's strongest advantage: paris headquarters gives EU-based clients a genuine EU legal entity for generative AI consulting work. InData Labs's strongest advantage: Founder's gaming background brings real-time data processing experience to computer vision work.
How do Capgemini Invent and InData Labs differ in pricing?
Capgemini Invent uses retainer, enterprise contracting pricing. InData Labs uses fixed project or dedicated team pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Capgemini Invent or InData Labs?
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 firm before shortlisting.
What are the main differences between Capgemini Invent and InData Labs?
Capgemini Invent's primary differentiator is: 17,000-plus person strategy and design brand backed by the wider Capgemini Group. InData Labs's primary differentiator is: data-science-first heritage predating the generative AI branding wave. They also differ in team size (17,000+ vs 51-200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Manufacturing vs Retail & e-commerce, Gaming).
Verify all details directly with each firm before making a decision.