Nexus vs Capgemini: Platform vs Scaled IT Delivery
Capgemini brings deep delivery capacity and European enterprise relationships. Nexus deploys production AI agents in weeks with FDEs. Full comparison.
Last updated: February 2026
Quick honest summary
Capgemini is one of the world's largest technology and consulting firms, with EUR 22.5B in revenue, 420,000+ employees across 50+ countries, and decades of experience delivering complex enterprise transformations. Their AI practice is growing fast (generative and agentic AI accounted for over 10% of revenues in 2025), and they bring genuine strengths: deep European roots, strong partnerships with Microsoft, Google Cloud, AWS, and (as of early 2026) OpenAI, plus massive nearshore and offshore delivery capacity that keeps costs lower than pure strategy firms. They recently announced AI-specific offerings spanning strategy, customer experience, software engineering, and custom enterprise AI. Capgemini has strong technical delivery capabilities and is a serious organization.
But there is a structural reality worth naming. Capgemini has genuine engineering and delivery capability; their technical teams can build real systems. However, large system integration projects are still managed by consulting and advisory leadership who scope, sell, and control engagements. In AI specifically, the gap between the advisory layer (who scopes and sells) and the technical layer (who builds) can slow delivery and inflate scope, even inside a firm with strong engineers. Beyond that, Capgemini's business model is built on billing days and hours. The longer a project runs, the more phases it requires, the more consultants involved, the more revenue the firm generates. This is not a criticism of individual consultants; it is how the economics of outsourcing and IT services work. The firm is incentivized to extend, not to compress. Complexity is not just a challenge to solve; it is a revenue driver.
Nexus is an enterprise AI agent platform paired with white-glove service: Forward Deployed Engineers embedded with your team, change management support, and ongoing optimization. It is not just software you buy and figure out on your own. Nexus is built for enterprises that need AI agents completing business workflows in production, with business teams owning the outcome. You do not pay for FDEs. Nexus is incentivized to deliver results quickly, because the commercial model depends on proving value within a 3-month POC before any annual commitment.
The choice comes down to a fundamental question: do you scale AI through headcount (more consultants, more sprints, more day rates) or through a platform (agents deployed in weeks, owned by your business teams, optimized continuously)?
Capgemini's model is assess, design, build, deliver, maintain. That is proven and works at scale for complex multi-system transformations. But it also means 6-18 month timelines, day-rate economics, and ongoing dependency on external teams for changes and maintenance. The structural incentive is toward longer, larger engagements. Nexus compresses that to 2-6 week POCs with measurable outcomes, per-agent pricing tied to value, and Forward Deployed Engineers who transfer ownership to your team rather than creating dependency.
Neither is universally better. The right choice depends on the scope, the urgency, and where you want ownership to live.
Side-by-side comparison
| Dimension | Capgemini AI | Nexus |
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| Handles exceptions? |
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| Security and compliance |
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| Ongoing evolution |
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When Capgemini is the better choice
Capgemini has real strengths, and there are scenarios where their model is the right approach. The key is ensuring the scope genuinely warrants the engagement model, rather than having the engagement model inflate the scope.
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You need large-scale systems integration, not just AI agents. If the project involves migrating ERPs, rebuilding data infrastructure, integrating dozens of legacy systems, and deploying AI as one component of a broader digital transformation, Capgemini can staff a program with hundreds of specialists across workstreams. That kind of multi-disciplinary, multi-year transformation is what large consulting firms are built for. The incentive misalignment matters less when the project genuinely requires that level of complexity.
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You are a European enterprise that wants a European partner with local presence. Capgemini is headquartered in Paris, deeply embedded in European enterprise ecosystems, and has strong relationships with European regulators and public institutions. For organizations where having a partner with a physical presence in your country, local language capability, and familiarity with regional regulatory environments matters, Capgemini's European footprint is a genuine advantage.
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You need a partner for both strategy and execution across your entire AI roadmap. If you are early in your AI journey and need help defining what to do (not just how to do it), Capgemini's Strategy and Transformation practice can help with assessment, roadmap development, and organizational readiness before any technology gets deployed. Just be clear-eyed about where strategy ends and where execution should begin, because the handoff is where timelines tend to expand.
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Your transformation involves complex multi-system orchestration requiring deep domain expertise. SAP migrations, cloud platform transitions, data lake architecture, and similar programs where Capgemini's experience with specific enterprise platforms adds genuine value. These are programs where domain-specific consulting expertise justifies the engagement model.
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You prefer a single vendor for everything. Some organizations want one partner accountable for strategy, design, implementation, and managed services. Capgemini's scale means they can own the entire lifecycle. That simplicity has value for procurement teams managing vendor complexity. The trade-off is that the firm controlling all phases also controls the pacing and scoping of all phases.
When Nexus is the better choice
Enterprises that partner with Nexus instead of (or alongside) a consulting firm tend to share a specific pattern: they have already invested in AI strategy, they know what workflows they want to automate, and they need production agents delivering measurable outcomes in weeks, not months. Often, they have experienced firsthand how the outsourcing model can stretch timelines far beyond what the problem actually requires.
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You have already spent on AI strategy. Now you need execution that delivers. Many Nexus customers have already been through a consulting engagement (with firms like Deloitte or McKinsey). They have the strategy deck. They have the roadmap. What they do not have is production AI agents generating financial outcomes. Nexus is built for the execution gap that strategy engagements leave behind. One example: an outsourcing firm at a Nexus client spent a full year in "project management mode," only finalizing planning for a first knowledge assistant. Twelve months of day rates, status meetings, and phase gates, with nothing in production. Nexus came in and delivered in 4 weeks: scrape, implement, push to production. That gap is not about competence. It is about incentive structure. The outsourcing firm was billing for time. Nexus needed to prove value.
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You cannot wait 6-18 months for results. Capgemini's model requires assessment phases, design phases, development sprints, testing cycles, and deployment. Each phase has its own timeline and cost, and each phase generates revenue for the firm. With Nexus, most agents go live within 2-6 weeks. Every engagement starts with a 3-month proof of concept tied to specific, measurable outcomes. You see results before committing to an annual contract.
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You want your business teams to own the agents, not depend on external consultants for every change. The consulting model creates a structural dependency: when the business changes, you go back to the consulting team, open a change request, wait for availability, and pay for more days. That dependency is not a bug in the consulting model; it is the business model. With Nexus, business teams own and iterate on agents directly. When Lambda's Head of Sales Intelligence needed to adjust data sources or account segmentation, he did it himself. No tickets. No backlog. No billable hours.
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You want per-agent pricing, not day rates. This is the core of the build vs buy question for enterprises. Capgemini charges for time (day rates, FTE equivalents, managed services contracts). The cost scales with how many people are involved and how long the engagement runs. The firm earns more when projects take longer. Nexus charges per agent, tied to value delivered. The cost scales with what the agents accomplish, not how many consultants are in the room. You do not pay for FDEs; Nexus is incentivized to deliver results quickly.
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You need Forward Deployed Engineers, not a rotating cast of consultants. Large consulting firms staff projects with teams that rotate. The senior partner who sold the deal may not be the person managing it. The architect who designed the solution may roll off after phase one. Nexus embeds Forward Deployed Engineers with your team for the duration. They know your systems, your workflows, your edge cases. They are not optimizing for utilization across multiple clients.
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You want enterprise governance included, not scoped as a separate workstream. Teams considering building with developer frameworks face this same challenge, needing to engineer compliance from scratch. In a consulting engagement, security, compliance, audit trails, and access controls are project deliverables with their own timelines and budgets (and their own day rates). With Nexus, SOC 2 Type II, ISO 27001, ISO 42001, and GDPR compliance are built into the platform from day one. Every agent decision is traceable. Every action is logged.
What enterprises experienced
Orange: EUR multi-billion telecom operator deployed in 4 weeks
Orange Group is a multi-billion euro telecom operator with 120,000+ employees across Europe and Africa. They have significant internal engineering resources and the budget to engage any consulting firm or build anything internally. They chose Nexus. While traditional IT consulting engagements run 6-18 months, Orange had agents in production before most firms finish the assessment phase.
Their business team (not engineering, not a consulting partner) built customer onboarding agents using the Nexus platform. Deployed across multiple European markets in 4 weeks. The results: 50% conversion improvement, $4M+ incremental yearly revenue, 100% team adoption, 100% compliance.
The timeline matters here. A consulting engagement for the same scope (multi-country customer onboarding automation with compliance requirements) would typically run 6-12 months through assessment, design, build, test, and deploy phases. Each phase billable. Each phase generating revenue for the firm. Orange was in production in 4 weeks. The difference is not just speed; it is what happens when the provider is incentivized to deliver outcomes rather than bill hours.
Lambda: a multi-billion dollar AI company chose platform over services
Lambda is an AI infrastructure company valued at $4B+ at its Series D, with a subsequent $1.5B+ Series E in late 2025, and $500M+ in annual revenue. They build supercomputers for AI training. They employ world-class AI engineers. If any company could either build internally or hire consultants to build for them, it was Lambda.
They chose neither. They chose Nexus.
Joaquin Paz, Lambda's Head of Sales Intelligence (not an engineer), built an autonomous research agent that monitors 12,000+ enterprise accounts annually, identifies buying signals, and synthesizes competitive intelligence. He built it in days.
The results: $4B+ in cumulative pipeline identified. 24,000+ research hours added annually (equivalent to 12 full-time analysts). Deployed in days, not the months a consulting engagement would require.
Lambda has since expanded from a single agent to a fleet across sales and marketing. Anticipated value: more than $7M by 2026.
"I'm not an engineer. I built this in days. With the automation tools we looked at before, I would have needed to spec everything out and wait months for development."
Joaquin Paz, Head of Sales Intelligence, Lambda
European telecom operator: compliance at enterprise scale
A multi-billion euro European telecom operator with 13,000+ employees built a multi-agent suite for support, compliance, and customer registration. 40% of support capacity freed. 100% compliance assurance with full audit trails. Deployed in 12 weeks, handling millions of customer interactions.
Key differences explained
Platform economics vs. services economics: different incentive structures
This is the core distinction, and it is worth understanding clearly.
Capgemini's model scales through headcount. More workflows to automate means more consultants, more sprints, more day rates. Each new AI capability requires a new engagement (or an extension of an existing one). The cost is proportional to the number of people involved and the duration of the work. This is where the structural incentive misalignment lives: the firm earns more when things take longer and involve more people. There is no natural pressure within the model to compress timelines or simplify scope. In fact, the opposite is true.
Nexus scales through a platform. Each new agent builds on the foundation already in place. Lambda went from one agent to an expanding fleet, with each new agent deploying in days rather than requiring a separate multi-month engagement. The 4,000+ pre-built integrations mean standard enterprise systems connect without custom project work. The cost scales with what agents deliver, not with how many people are building them. Nexus only converts POCs to annual contracts when measurable value is proven, which means the incentive is to deliver results as fast as possible.
For a single, narrowly scoped AI project, the cost difference may be modest. For an enterprise that wants to deploy agents across sales, marketing, support, and HR, the compounding difference between platform economics and services economics becomes significant. Under the consulting model, each new use case is a new revenue opportunity for the firm. Under the platform model, each new agent is incremental value on the same foundation.
Forward Deployed Engineers vs. consulting teams: aligned vs. misaligned incentives
Capgemini consultants are skilled professionals. But the consulting model creates a structural tension that no amount of good intention can fully resolve: the firm is incentivized to extend engagements and expand scope, because revenue is driven by billable days. The people who understand your system best are employed by the consulting firm, not by you. Their continued involvement is how the firm earns. Knowledge transfer is always promised; dependency is what the business model rewards.
Nexus Forward Deployed Engineers are embedded with your team, but the goal is the opposite of dependency. FDEs are builders in control: they implement directly on a full-stack platform, with no coordination layer between the person defining the solution and the person building it. FDEs help identify the highest-impact use cases, design agents that fit your specific reality, handle integration complexity, and manage change. But they transfer ownership to your business teams. You do not pay for FDEs separately. The measure of success is not how many days they bill; it is whether the POC converts to an annual contract, which only happens if measurable value is delivered. The incentive is aligned: Nexus succeeds when you succeed quickly. That is why Nexus converts 100% of POCs to annual contracts.
Time to value: weeks vs. quarters, and why the gap exists
A typical Capgemini AI engagement follows a structured methodology: discovery and assessment (4-8 weeks), solution design (4-6 weeks), development and integration (8-16 weeks), testing and deployment (4-8 weeks), stabilization and handover (4-6 weeks). Total: roughly 6-12 months for a well-scoped engagement, longer if the scope expands. Each of those phases is a billable workstream. The methodology is thorough, but the incentive is not to compress it.
With Nexus, most enterprise agents go live within 2-6 weeks. Orange deployed customer onboarding agents across multiple European markets in 4 weeks. Lambda's first agent was live in days. The difference is not that Nexus cuts corners; it is that Nexus has no incentive to stretch timelines.
The gap compounds when you move beyond a single use case. Each new Capgemini engagement requires its own lifecycle (and its own revenue stream for the firm). Each new Nexus agent builds on the foundation already in place. Lambda expanded from a single agent to a fleet, with each subsequent agent deploying faster than the last.
The strategy-to-execution gap: where complexity inflation happens
Many enterprises that come to Nexus have already worked with consulting firms. They have strategy decks, roadmaps, and transformation visions. What they do not have is production AI agents generating financial outcomes.
This is where a pattern we call "complexity inflation" emerges. Large system integrators like Capgemini are skilled at making problems feel more complex than they are. Not out of malice, but because the business model rewards it. A client that needs a working agent in production gets scoped into a multi-year transformation program with discovery phases, architecture reviews, platform selection workstreams, and governance committees. The problem was real but bounded; the solution becomes sprawling because sprawl generates more billable days.
One Nexus client experienced this directly: an outsourcing firm spent a full year in project management mode, only finalizing planning for a first knowledge assistant. Twelve months, no production deployment. Nexus delivered a working agent in 4 weeks. The problem was never as complex as the engagement made it feel.
This is not a criticism of consulting strategy work. It is a structural observation. Nexus is built for the execution layer. If Capgemini (or another firm) has already defined your AI strategy and identified priority use cases, Nexus can move directly to production agents in weeks. The two approaches can be complementary: strategy from a consulting firm, execution from a platform with embedded engineering support. Just be cautious about letting the strategy phase expand indefinitely, because the firm executing it has no structural incentive to end it.
Frequently asked questions
Can we use Nexus alongside an existing Capgemini engagement?
Yes. Some enterprises use consulting firms for broader digital transformation programs (systems integration, data infrastructure, organizational change) and Nexus specifically for AI agent deployment. The two solve different problems at different speeds. If Capgemini is handling your ERP migration or cloud platform transition, Nexus can run in parallel to deploy production AI agents on the workflows that are ready now, rather than waiting for the broader program to complete. In practice, this also gives you a useful benchmark: you can compare the velocity and cost of platform-based agent deployment against consulting-led delivery running in parallel.
Capgemini has 420,000+ employees. How can Nexus compete on delivery capacity?
Nexus does not compete on headcount. That is the point. In a services model, more headcount means more billable capacity, which is good for the firm. But the question for the client is whether AI agent deployment requires hundreds of consultants or a platform with embedded engineering support. For large-scale systems integration, Capgemini's scale matters. For deploying AI agents that complete business workflows, a platform approach with Forward Deployed Engineers delivers faster outcomes with lower ongoing cost. Lambda deployed agents in days that would have taken a large team months to build. Headcount is an asset for the consulting firm; it is a cost for the client.
Capgemini just partnered with OpenAI, Google Cloud, and Microsoft on AI. Does that change things?
Capgemini's partnerships with major AI providers strengthen their ability to build custom solutions using those vendors' technologies. But the underlying model has not changed: their teams design and build the solution using vendor tools, and you pay for that delivery time. Better tools in the hands of the same incentive structure still produce the same dynamics: day-rate billing, extended timelines, and dependency on the consulting team. Nexus is model-agnostic (works with any AI model), has 4,000+ pre-built integrations, and deploys agents through a platform, not through project-based custom development. The partnerships make Capgemini's custom builds potentially stronger, but they do not change the timeline, cost, or ownership dynamics.
Is Nexus cheaper than Capgemini?
For AI agent deployment specifically, yes, typically by a significant margin. A Capgemini engagement for a comparable scope (multi-system AI agent with compliance, deployed across channels) would involve multiple consultants over several months at day rates. Under that model, you pay for effort; the firm earns more when the effort is larger and longer. Nexus delivers the same outcome through a platform in weeks, with per-agent pricing tied to what agents deliver. The 3-month POC lets you measure actual cost against actual value before committing. For a broader digital transformation program that includes systems integration, data migration, and organizational restructuring, the comparison is not direct because Nexus does not do those things.
We have been burned by consulting firms before. How is Nexus different?
Most consulting disappointments trace back to the same root cause: the firm was incentivized to bill time, not deliver outcomes. Longer timelines, expanding scope, growing dependency: these are not failures of the consulting model; they are the consulting model working as designed, for the firm.
Nexus is structurally different in three ways. First, the 3-month POC is tied to specific, measurable outcomes defined upfront. You see results before committing to anything longer. Second, Forward Deployed Engineers are embedded with your team to transfer ownership, not to create dependency. You do not pay for FDEs separately. Third, per-agent pricing means you pay for what agents deliver, not for how many days people work. The 100% POC-to-contract conversion rate exists because Nexus does not move forward unless the value is clear. The incentives are aligned with yours.
What if we need both strategy and execution?
If you need someone to define your AI strategy from scratch (which use cases to prioritize, how to organize your AI program, what the roadmap should look like), a consulting firm can do that. Where Nexus excels is execution: taking identified use cases and deploying production agents that deliver measurable outcomes in weeks. Some enterprises work with a consulting firm for strategy and Nexus for deployment. Others come to Nexus after the strategy phase is complete and they are ready to execute. The important thing is to keep the strategy phase bounded. Consulting firms are not incentivized to end it; you need to be the one who draws that line.
Does Nexus work for regulated European enterprises?
Yes. Nexus is SOC 2 Type II, ISO 27001, ISO 42001, and GDPR certified. Full audit trails, decision traceability, and role-based access are built in from day one. Orange, a public European telecom operator, deployed agents with 100% compliance. The platform is headquartered in Brussels with offices in San Francisco, giving it direct European presence and understanding of European regulatory environments.
Worth exploring?
If your team has been evaluating consulting firms for AI deployment and weighing the trade-offs (6-18 month timelines, day-rate economics, ownership that stays with the consulting partner, scope that keeps expanding), it might be worth seeing how enterprises like Orange and Lambda approached the same decision. Or consider the client whose outsourcing firm spent a full year planning a knowledge assistant that Nexus delivered in 4 weeks.
Orange is a multi-billion euro telecom operator with 120,000+ employees. They deployed customer onboarding agents in 4 weeks. 50% conversion improvement. $4M+ incremental yearly revenue. 100% adoption. Business teams own it.
Lambda is a multi-billion dollar AI infrastructure company with world-class engineers. They concluded that the opportunity cost of building (or having someone build for them) was too high. They deployed in days what would have taken months. Anticipated value: more than $7M by 2026.
Every Nexus engagement starts with a 3-month proof of concept tied to specific outcomes. Forward Deployed Engineers work alongside your team from day one. You do not pay for FDEs. You see results before committing. You can exit anytime. The incentive is simple: Nexus only wins a contract when you see measurable value first.
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Every engagement starts with a 3-month proof of concept tied to specific, measurable business outcomes. Forward Deployed Engineers embed with your team from day one.