Capgemini vs STX Next: full comparison for 2026
Quick verdict
Capgemini (4.0/5) edges ahead of STX Next (4.0/5) overall. Capgemini is the better choice for global firms outsourcing AI-run back-office processes. STX Next is the stronger option for python-heavy product teams. The right choice depends on your project size, budget, and required tech stack.
Capgemini vs STX Next: head-to-head summary
| Criterion | Capgemini | STX Next |
|---|---|---|
| Founded | 1967 | 2005 |
| HQ | Paris, France | Poznań, Poland |
| Team size | 340,000+ | 250–999 |
| Rating | 4.0 / 5 | 4.0 / 5 |
| Primary differentiator | Business-process outsourcing combined with agentic AI after the WNS deal | Python engineering depth applied to AI and data work |
| Pricing model | Outcome-based BPS contracts, fixed-scope programs, and managed services; rates on request | Time & materials and dedicated teams; $50–$99/hr (Clutch band) |
| Min. engagement | Not disclosed | $50,000+ (Clutch) |
| Primary tech stack | SAP, Salesforce, Microsoft Dynamics 365 | Python, Databricks, Snowflake |
| Industries served | Manufacturing, Financial services, Insurance, Energy, Public sector | Financial services, Energy, Manufacturing, Healthcare, SaaS |
Capgemini vs STX Next: overview
Capgemini
Capgemini is a French IT services and consulting group founded in 1967, with more than 340,000 employees before its latest acquisition. It completed the $3.3 billion purchase of WNS, a business-process services firm, in October 2025, with the stated aim of selling agentic AI-run operations: finance, customer service, and procurement processes partly executed by agents. Its earlier acquisition of engineering firm Altran (2020) adds industrial depth. Buyers get global SAP, Salesforce, and Microsoft practices under one contract.
STX Next
STX Next was founded in 2005 in Poznań and grew into one of Europe's largest Python engineering firms, with 250–999 staff according to Clutch. Clutch puts about 60% of its listed work in AI development and another 15% in generative AI, and it lists a 4.7 rating from 101 reviews as of July 2026. Python-first teams are a natural match because the integration code fits their existing stack. Clutch shows a $50–$99 hourly band and a $50,000 minimum.
Services and capabilities: Capgemini vs STX Next
| Capability | Capgemini | STX Next |
|---|---|---|
| CRM / ERP integration | ✓ | ✗ |
| LLM API gateway & cost control | ✗ | ✓ |
| Document processing | ✗ | ✗ |
| Conversational AI | ✗ | ✗ |
| Agentic workflows | ✓ | ✓ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✓ | ✗ |
Tech stack comparison: Capgemini vs STX Next
| Framework / platform | Capgemini | STX Next |
|---|---|---|
| Salesforce | ✓ | N/A |
| SAP | ✓ | N/A |
| Microsoft Dynamics 365 | ✓ | N/A |
| HubSpot | N/A | N/A |
| Snowflake | N/A | ✓ |
| Databricks | N/A | ✓ |
| BigQuery | N/A | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | N/A | ✓ |
| Zendesk | N/A | N/A |
Pricing comparison: Capgemini vs STX Next
| Criterion | Capgemini | STX Next |
|---|---|---|
| Minimum engagement | Not disclosed | $50,000+ (Clutch) |
| Engagement models | Fixed-scope project, Managed services | Dedicated team, Time & materials |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Capgemini vs STX Next
| Dimension | Capgemini | STX Next |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Manufacturing, Financial services, Insurance | Financial services, Energy, Manufacturing |
| Best use cases | Agent-assisted accounts payable run as a managed process, AI features in SAP S/4HANA programs | Extending a Python product team with LLM engineers, Data platform work for energy and fintech clients |
| Typical project type | Fixed-scope project | Dedicated team |
Capgemini vs STX Next: pros and cons
| Capgemini | |
|---|---|
| + | Can take over an entire process, not just build the integration. |
| + | SAP depth for AI inside finance and supply chain. |
| + | Altran engineering heritage for industrial clients. |
| + | Global delivery for multi-country rollouts. |
| - | Integrating WNS (acquired October 2025) is still under way |
| - | Outsourcing-style contracts are long and heavy for a first AI test |
| - | Pricing is rarely competitive for a single-workflow pilot |
| STX Next | |
|---|---|
| + | Python is the language of most AI tooling, and it's the firm's core skill. |
| + | 101 Clutch reviews give a broad base of client feedback. |
| + | Reviewers frequently mention responsiveness and on-time delivery. |
| - | The $50K Clutch minimum is high for a first experiment |
| - | No CRM or ERP partner credentials |
| - | Some reviews mention weaker documentation and onboarding |
Who should choose Capgemini?
A typical fit: agent-assisted accounts payable run as a managed process.
Business-process outsourcing combined with agentic AI after the WNS deal. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Financial services, Insurance, Energy, Public sector.
Who should choose STX Next?
A typical fit: extending a Python product team with LLM engineers.
Python engineering depth applied to AI and data work. Minimum engagement starts at $50,000+ (Clutch). Works best with clients in Financial services, Energy, Manufacturing, Healthcare, SaaS.
Decision matrix: Capgemini vs STX Next
| Your situation | Recommended choice |
|---|---|
| You want a priced pilot before committing to a rollout | Neither advertises one; ask for a scoped pilot quote |
| You need someone to run and monitor the system after launch | Capgemini |
| Your budget is at the lower end | Compare: Capgemini (Not disclosed) vs STX Next ($50,000+ (Clutch)) |
| The AI has to read and write in your CRM or ERP | Capgemini |
| You need multi-step agents acting across systems | Both build agentic workflows |
| You need a large team for a multi-year program | Capgemini |
Use case fit: Capgemini vs STX Next
| Use case | Capgemini fit | STX Next fit | Winner |
|---|---|---|---|
| Agent-assisted accounts payable run as a managed process | Strong | Limited | Capgemini |
| AI features in SAP S/4HANA programs | Strong | Limited | Capgemini |
| Extending a Python product team with LLM engineers | Limited | Strong | STX Next |
| Data platform work for energy and fintech clients | Limited | Strong | STX Next |
Verdict: Capgemini vs STX Next
Capgemini (4.0/5) is the stronger overall choice for most AI Integration Services projects. Business-process outsourcing combined with agentic AI after the WNS deal.
STX Next (4.0/5) is worth a look if you need data platform work for energy and fintech clients. If your situation matches that, STX Next is a competitive option.
Related comparisons
Capgemini vs STX Next FAQ
Is Capgemini better than STX Next?
Capgemini (4.0/5) scores higher overall, but "better" depends on your use case. Capgemini's strongest advantage: can take over an entire process, not just build the integration. STX Next's strongest advantage: python is the language of most AI tooling, and it's the firm's core skill.
How do Capgemini and STX Next differ in pricing?
Capgemini's pricing: outcome-based BPS contracts, fixed-scope programs, and managed services; rates on request. STX Next's pricing: time & materials and dedicated teams; $50–$99/hr (Clutch band) with a minimum engagement of $50,000+ (Clutch). Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: Capgemini or STX Next?
Capgemini is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each provider before shortlisting.
What are the main differences between Capgemini and STX Next?
Capgemini's primary differentiator is: business-process outsourcing combined with agentic AI after the WNS deal. STX Next's primary differentiator is: python engineering depth applied to AI and data work. They also differ in team size (340,000+ vs 250–999), minimum engagement (Not disclosed vs $50,000+ (Clutch)), and primary industries served (Manufacturing, Financial services vs Financial services, Energy).
Verify all details directly with each provider before making a decision.