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 AI strategy services from a Paris-headquartered firm. InData Labs is the stronger option for teams needing data science advisory services before an 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 | A 17,000-plus person services brand backed by the larger Capgemini Group | A data-science-first service 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 out of Paris as the digital innovation, consulting, and transformation services brand of the wider Capgemini Group, and it now employs somewhere between roughly 17,000 and 18,000-plus people across six continents depending on the source. Its service catalog combines strategy with data science and design under a single brand, treating AI as a component of digital transformation rather than a standalone service line.
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 service catalog centers on data science advisory, predictive analytics, natural language processing, and computer vision, positioning it closer to a data-first services firm than a generative-AI-branded competitor.
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 AI strategy service with an EU-incorporated vendor., Pairing AI services with a broader digital transformation and design initiative. | Getting a data science advisory service before committing to a full AI build., Adding computer vision strategy services 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 | |
|---|---|
| + | A Paris headquarters gives EU clients a genuine EU legal entity to sign a services contract with. |
| + | 17,000-plus staff across six continents supports large, distributed service programs. |
| + | Can escalate into the wider Capgemini Group's delivery capacity once a service scales up. |
| + | Strategy consulting, data science, and design all sit under a single services brand. |
| - | AI service work is folded into a broader digital transformation brand rather than sold as its own line |
| - | Reported staff counts differ by roughly 1,000 across public sources |
| InData Labs | |
|---|---|
| + | The founder's gaming background brings real-time data processing experience to computer vision services. |
| + | A Cyprus headquarters (EU-based) can simplify GDPR-aligned data handling for European clients. |
| + | Predictive analytics and NLP services predate the current generative AI wave. |
| + | More than a decade of track record in a narrower, more defensible service 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 AI strategy service with an EU-incorporated vendor.
A 17,000-plus person services brand backed by the larger 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 advisory service before committing to a full AI build.
A data-science-first service 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 AI strategy service with an EU-incorporated vendor. | Strong | Strong | Both equally |
| Pairing AI services with a broader digital transformation and design initiative. | Strong | Limited | Capgemini Invent |
| Getting a data science advisory service before committing to a full AI build. | Limited | Strong | InData Labs |
| Adding computer vision strategy services 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 AI Consulting projects. A 17,000-plus person services brand backed by the larger Capgemini Group.
InData Labs (3.9/5) is worth a look if you need adding computer vision strategy services 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: a Paris headquarters gives EU clients a genuine EU legal entity to sign a services contract with. InData Labs's strongest advantage: the founder's gaming background brings real-time data processing experience to computer vision services.
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: a 17,000-plus person services brand backed by the larger Capgemini Group. InData Labs's primary differentiator is: a data-science-first service 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.