Report:

Magic Quadrant for Custom Software Development Services

Top Vendor Products for Custom Software Development Services in 2025

• Accenture
• Capgemini
• Cognizant
• Deloitte
• EPAM
• HCLTech
• IBM
• Infosys

Custom Software Development Services Vendor Product Comparisons 2025

• Accenture - Leader
  

  Pros:

  • AI-native engineering at scale: Accenture has implemented AI-native engineering practices across the SDLC, supported by proprietary agent marketplaces, cognitive enterprise frameworks, and a global workforce of approximately 129,000 professionals, driving 30% to 40% productivity gains for complex custom development and modernization projects.
  • End-to-end industry context: Accenture leverages deep industry expertise and a broad partner ecosystem to deliver context-aware solutions across the value chain. The company has proven its ability to lead major transformations, including complex mainframe migration and AI platform implementation, through close client and partner collaboration.
  • Talent transformation and nonlinear value delivery: Accenture invests in upskilling (for example, it acquired online education provider Udacity in 2024) and shifts talent toward business-aligned roles, integrating AI agents to automate routine work.

  Cons:

  • Early-stage pricing models: Accenture is piloting outcome-based and agent-based pricing. However, with only 5% of CSD revenue from outcome-based contracts — a figure below the evaluated group average of 11% — clients interested in innovative pricing are encouraged to discuss options early and indicate their preferences.
  • Integration complexity and change management: Accenture's focus on large-scale transformations, often leveraging advanced AI agents and cognitive frameworks, may introduce integration complexity for clients with intricate legacy environments.
  • Workforce evolution and talent recalibration: Accenture's adoption of AI agents and other advanced technologies will lead to changes in talent composition, requiring the recalibration of workforce skills and roles.


• Capgemini - Leader
  

  Pros:

  • Agentic AI platform-led delivery: Capgemini has integrated agentic and generative AI into key software development processes via proprietary frameworks and advanced multiagent orchestration. Through 2024, large language model (LLM)-based agents were used in a majority of client projects, with a considerable portion of AI-generated code.
  • Flexible commercial models: Capgemini offers a mix of outcome-based and hybrid contracts, representing approximately 40% of its CSD revenue.
  • Industry and regulatory expertise: Capgemini's sector-focused teams and governance frameworks support clients in regulated industries. The company conducts deal-level CISO reviews in CSD engagements and aligns with regulations such as the EU AI Act.

  Cons:

  • Limited North American resource pool: While only 10% of Capgemini's custom software development workforce is based in North America (which is below the peer group average of 51%), approximately 25% of its global resources are dedicated to North American clients.
  • Senior talent pool: Approximately 20% of Capgemini's CSD full-time equivalents (FTEs) have more than 10 years of experience, which is slightly below the peer group average.
  • Decline in CSD revenue and FTE growth: Capgemini has reported a slight decline in CSD revenue growth rates and headcount in recent quarters, which may indicate near-term resourcing constraints.


• Coforge - Niche Player
  

  Pros:

  • Focused domain specialization: Coforge has deep vertical expertise in the banking, insurance, and travel industries, driving approximately 70% of its revenue from clients in those verticals.
  • Proprietary delivery platforms: Coforge has developed proprietary engineering platforms (Forge-X) and AI-enabled tools, including BlueSwan, CodeInsightAI, and EvolveOps.AI, to support delivery consistency and transformation initiatives.
  • Workforce expansion and project pipeline: Coforge's FTE count increased by 46%, the highest growth rate among its evaluated peers.

  Cons:

  • Proprietary platform-centric approach: Coforge's differentiation relies substantially on its proprietary engineering platforms, which are built using open-source standards and frameworks. However, these platforms may not always align seamlessly with diverse client technology stacks or integration needs.
  • Limited industry expertise: Coforge's CSD portfolio is still concentrated in a few verticals — notably banking, financial services, and insurance (BFSI) and travel — which limits cross-industry diversification.
  • Experience mix and offshore delivery concentration: Eighty percent of Coforge's delivery workforce is offshore, with 43% of those workers having less than five years' experience.


• Cognizant - Leader
  

  Pros:

  • Strong digital engineering: Cognizant excels at integrating advanced technologies — such as AI, machine learning (ML), the Internet of Things (IoT), and cloud computing — into custom software solutions, while simultaneously focusing on enhancing user experience and business outcomes.
  • Enterprise-scale industry focus: Cognizant has experience executing large-scale digital transformation projects, combining custom software engineering with commercial solutions. The company has domain expertise in sectors that include manufacturing, healthcare, and communications.
  • Talent development and responsible AI: Cognizant's workforce strategy includes ongoing upskilling, with over 70% of delivery staff trained in AI and modern engineering practices. The company has adopted an ISO 42001-certified responsible AI framework.

  Cons:

  • New client acquisition: Cognizant's rate of acquiring new clients is below the peer average of 15%. Given the project needs of its clients, Cognizant has intentionally focused on its existing customer base.
  • Delivery model balance: Cognizant's delivery model relies primarily on offshore resources (76%), which supports efficiency and scalability. This approach may present challenges for clients that require more localized or collaborative engagement.
  • Pricing approach: While Cognizant offers competitive pricing, clients are encouraged to ensure that contracts are structured around clear strategic objectives and measurable outcomes for their custom software engagements.


• Deloitte - Leader
  

  Pros:

  • AI and engineering investments: Deloitte has committed and invested a significant portion of its revenue to AI and GenAI, using proprietary platforms like AI Assist to automate workflows and accelerate prototyping throughout the software development life cycle.
  • Industry expertise and multidisciplinary approach: Deloitte's IndustryAdvantage program integrates deep sector knowledge with technology, drawing on expertise from finance, supply chain, human capital, tax, and cybersecurity.
  • Contracting and commercial flexibility: Deloitte offers flexible, outcome-based contracts (above the peer group average), along with milestone payments and value-based billing.

  Cons:

  • Not suited for tactical/flexible staffing deals: With only a limited portion of CSD revenue coming from staff augmentation, Deloitte is built for large, longer-term, outcome-driven programs rather than flexible resourcing.
  • Challenges with traditional buyers and RFPs: Deloitte's lab-based, rapid prototyping methodology may limit the company's opportunity to apply it to conventional procurement processes or buyers/organizations that prefer traditional procurement models.
  • Inconsistent geographic experience and delivery: Gartner client feedback via inquiries suggests that the Deloitte customer experience might not always be uniformly positive across all regions.


• Endava - Niche Player
  

  Pros:

  • Focused AI integration across offerings: Endava has made a deliberate shift to embed AI into its core services, with organizationwide training and proprietary accelerators such as Morpheus and Compass.
  • Selective global delivery and talent development: Endava offers a balanced delivery model, leveraging nearshore and offshore resources as needed, and invests in developing AI-focused talent through targeted university hiring.
  • Evolving advisory and consulting capabilities: While historically engineering-led, Endava is expanding its advisory and consulting services, supported by recent acquisitions and senior hires.

  Cons:

  • Recent growth volatility, market headwinds, and transformation efforts: Endava experienced a revenue decline in the last fiscal year. In response, Endava has undertaken efforts to transform into an AI-native company.
  • Dependence on existing account expansion: Endava's growth strategy is heavily reliant on increasing its share of wallet within existing accounts, with less emphasis on net-new client acquisition.
  • Limited differentiation in delivery model: Endava's nearshore and offshore delivery models mirror industry norms and no longer offer a competitive advantage.


• EPAM - Leader
  

  Pros:

  • Proven business impact in complex industries: EPAM has a track record of delivering tangible business outcomes in regulated industries by building custom software solutions.
  • Engineering excellence and quality: EPAM applies agile and DevOps methodologies, supported by data-driven governance frameworks, to deliver complex custom software projects at scale.
  • IP-driven acceleration and ecosystem leverage: EPAM's AI accelerators (DIAL and QuantHub) automate orchestration and data engineering in custom software development, enabling up to 30% faster delivery and rapid monetization.

  Cons:

  • Multiexperience capabilities in a rapidly advancing market: While some leaders in this study presented case studies demonstrating an exhaustive multiexperience approach, EPAM highlights multiexperience development as a capability, with particular strength in web and mobile.
  • Adapting engagement models: EPAM's shift toward co-investment and outcome-based engagements may be ahead of some clients transitioning from traditional models.
  • Integration of acquisitions: EPAM's acquisition strategy has broadened its CSD capabilities, but integrating these assets into a seamless, differentiated offering is an ongoing process.


• GlobalLogic - Niche Player
  

  Pros:

  • AI usage in client projects: GlobalLogic adopts an AI-first approach to software development, leveraging proprietary tools such as VelocityAI to integrate AI capabilities throughout the project life cycle.
  • Engineering and ecosystem integration: GlobalLogic draws on its Silicon Valley background and Hitachi's global resources to address complex custom-build needs, with a focus on telecom, healthcare, and energy.
  • Strong presence among small clients: GlobalLogic reported that roughly 47% of its CSD services revenue comes from small clients (organizations with fewer than 999 employees).

  Cons:

  • Market breadth: GlobalLogic has limited experience in verticals such as retail, consumer packaged goods, government/public sector, and traditional financial services.
  • Limited pool of senior talent: Given that roughly 76% of GlobalLogic's CSD FTEs have less than five years' experience and only 7% possess 10 years or more, there is a potential risk of limited deep domain expertise.
  • Limited adoption of outcome-based contracts: Sixty-nine percent (among the highest in this cohort) of GlobalLogic's CSD client engagements are structured as T&M contracts, while only 7% (below the group average) are tied to business outcomes.


• Globant - Challenger
  

  Pros:

  • Nearshore proximity strength: Globant has a strong Latin America nearshore presence, with 67% of its CSD FTEs based in that region (the highest percentage in this study).
  • Strong vertical plays: Globant is particularly strong in the communications, media, and services verticals (which includes high tech), along with financial and professional services.
  • Industry-focused studio model: Globant has strategically realigned its operations and P&L around industry-specific AI Studios (such as finance, media and entertainment, airlines, healthcare and life sciences, and retail).

  Cons:

  • Evolving engagement models and traditional pricing: While Globant's AI Pods model is gaining attention, 73% of its CSD services revenue still comes from deals under $500,000 and relies on traditional T&M frameworks.
  • Recent scaling of industry alignment: Globant's verticalization and business consulting depth are relatively recent, with a stronger presence in media, entertainment, and financial services than in energy/utilities, manufacturing, or the public sector.
  • Limited integration of design in CSD: Design is explicitly leveraged in only 18% of Globant's CSD deals, and its number of design-focused FTEs (around 670) is small relative to the total CSD FTEs (over 25,000).


• HCLTech - Leader
  

  Pros:

  • Unique 'chip to cloud' capability: HCLTech offers capabilities spanning from hardware design to cloud solutions — a rare distinction among large IT services providers.
  • Outcome-based commercial models: HCLTech is moving toward flexible, outcome-based contracts — 25% of its contracts now follow this model, which is above the group average.
  • Strategic industry alignment and repeatable solutions: HCLTech has made a deliberate shift to organize its client-facing teams by global industry verticals, ensuring sharper, context-rich engagement.

  Cons:

  • Brand awareness for CSD: The market still perceives HCLTech to be stronger in its infrastructure business, and further work is needed to establish stronger brand awareness and market perception, specifically for its CSD services.
  • Newness of key strategic partnerships: While HCLTech has forged strategic partnerships with entities like OpenAI, this particular collaboration is very new.
  • Integration and complexity risk from IP/platform proliferation: HCLTech's rapid investment in, and proliferation of, proprietary intellectual property (IP) and platforms is a strength for innovation, but it could introduce integration and complexity risks for clients.


• IBM - Leader
  

  Pros:

  • Open innovation and technology agnosticism: IBM combines proprietary assets with a pragmatic, client-focused approach, embracing best-of-breed, third-party, and open-source technologies.
  • Proven methodologies for accelerated value: The IBM Garage methodology and Consulting Advantage platform are recognized for accelerating transformation, which IBM states are delivering five to seven times more value.
  • Flexible commercial models and commitment: IBM shares risk and reward through innovative financial models like revenue sharing, value-based modernization, and shared IP.

  Cons:

  • Prioritizing technology over business context: IBM's strong emphasis on AI in every engagement may lead to solutions that are technology-focused rather than business-centric.
  • Scale and process rigor: IBM's enterprise-scale governance, operating models, and global delivery centers are strengths for large, complex programs, but they can introduce overhead or slow decision making.
  • IBM technology stack preference: Despite the company's stated openness, there is a visible infusion of IBM products and platforms across case studies, raising concerns about implicit bias or long-term proprietary dependencies.


• Infosys - Leader
  

  Pros:

  • Distinct CSD focus: Infosys derives 58% of its overall revenue from CSD — the second highest among full-service peers in this study.
  • Strategic-level engagement model: Infosys effectively addresses complex business- and technology-driven custom-build challenges, as evidenced by its client case studies.
  • Responsible AI integration: Infosys goes beyond basic compliance by embedding security, privacy, and responsible AI practices into its software development.

  Cons:

  • Market penetration: Buyers in Western Europe and Japan — and from midsize organizations — should note that Infosys has less presence and lower CSD revenue in these segments.
  • Traditional client/governance structures: Infosys faces challenges aligning its agile practices with clients that prefer traditional governance models, such as fixed milestones and detailed requirements.
  • Stand-alone IP monetization: Infosys recognizes that effectively monetizing its IP and platforms — such as Topaz and Helix — as stand-alone products in alignment with client interests is an area for improvement.


• NTT DATA - Challenger
  

  Pros:

  • AI-enabled engineering: NTT DATA is taking an AI-first approach to software design and development, leveraging its aXet platform to support GenAI and agentic AI workflows.
  • Strong partner ecosystem: NTT DATA's expanded alliances — with AI-driven startups through its venture capital (VC) program and with industry leaders such as AWS, Google, Microsoft, and NVIDIA.
  • Growth acceleration: Following the merger of NTT DATA and NTT Ltd, the company has made several acquisitions to expand its capabilities.

  Cons:

  • Postmerger integration challenges: Postmerger integrations at NTT DATA can prolong the alignment of teams, tools, and processes.
  • Clarity in business outcome articulation: NTT DATA generates 23% of its CSD services revenue (which is above the group average) by tying solutions to business outcomes. However, in some case study presentations, the link between its technical work and direct user or business impact is not always clear.
  • Limited offshore/nearshore leverage: Compared with its peers, NTT DATA has fewer CSD resources in places like India, Eastern Europe, and South America.


• Persistent Systems - Challenger
  

  Pros:

  • AI-first, platform-driven approach: Persistent integrates AI across the software development life cycle using its proprietary platforms — SASVA, iAURA, and GenAI Hub.
  • Consistent growth and viability: Persistent's 20 consecutive quarters of growth and 24% compound annual growth rate (CAGR) over four years reflect strong financial health and stability.
  • Talent upskilling: Persistent has invested in upskilling its workforce on GenAI by leveraging a role-based learning framework and targeted training model.

  Cons:

  • Limited outcome-based engagements: Persistent generates only 3.7% of its CSD services revenue from business-outcome-based engagements, with the bulk (68.2%) still tied to time-and-materials models.
  • Design and user experience capabilities in a competitive landscape: Compared with the cohort, Persistent demonstrates particular strength in delivering technical improvements. Notably, the percentage of Persistent's engagements that were design-centric was 45%, which is below the group average.
  • Strategic transformation capabilities among industry peers: Compared to the cohort — where some leaders demonstrated strong capabilities in driving strategic, greenfield, or complex transformations — Persistent is frequently recognized as a capable execution partner.


• SoftServe - Niche Player
  

  Pros:

  • High-impact and emerging technologies: SoftServe maintains a robust technology and engineering focus, prioritizing investment in high-value, emerging areas such as AI, GenAI, cloud engineering, data, digital twins, simulations, and robotics.
  • Talent development and engineering excellence: SoftServe recruits talent from the top 20% of the market distribution and invests in continuous upskilling, reskilling, and internal mobility.
  • Nearshore advantage: With 91% of its CSD talent based in Eastern Europe, SoftServe delivers true nearshore scale.

  Cons:

  • Growth momentum concerns: SoftServe's CSD practice has seen revenue and FTEs decline, signaling pressure on its core growth engine.
  • Predominant reliance on traditional engagement models: SoftServe's use of alternative and outcome-based pricing represents a very small fraction of its deals (3% outcome-based, 7% fixed price).
  • Approach to junior talent development: SoftServe's workforce rebalancing involved laying off junior talent in favor of retaining senior staff in high-impact areas such as AI and cloud.


• Softtek - Challenger
  

  Pros:

  • Talent stability: With a low attrition rate of 8% (below the group average), the company demonstrates strong talent retention and team continuity.
  • Industry expertise and specialized delivery: Softtek operates 10 dedicated industry specialty groups, each supported by its own center of excellence, industry subject matter experts and innovation solution labs.
  • Strength in midsize client segment: Softtek derives approximately 36% of its revenue from midsize clients (above the group average).

  Cons:

  • Limited Asia/Pacific reach: Softtek derives only around 4% of its CSD revenue and has just 8% of its CSD FTEs in Asia/Pacific, highlighting thin regional penetration and delivery depth.
  • Unproven innovation scaling and adoption: Despite significant investment in AI tools, upskilling, and proprietary platforms such as FRIDA, there is a lack of clear proof points regarding the adoption and impact of these innovations.
  • Ongoing transition to outcome-based engagements: Forty-four percent of Softtek's CSD engagements remain on T&M contracts.


• Tata Consultancy Services - Challenger
  

  Pros:

  • High engineering process discipline: TCS' disciplined delivery frameworks — agile at scale, ISO-certified processes, and CMMI Level 5 maturity — are tuned for custom software development.
  • Long-tenure client relationships: Ten to 15+ year partnerships with major clients underscore TCS' ability to deliver custom software solutions that adapt and scale as clients' needs evolve.
  • Scale as a strategic advantage: TCS' vast scale empowers the company to rapidly assemble and deploy expert software engineering teams tailored to each client's specific technology stack and project requirements.

  Cons:

  • Lack of delivery agility: While TCS' scale benefits large, complex projects, it can add governance layers that slow response in fast-changing, agile programs.
  • Design-led innovation is less differentiated: TCS excels in engineering and delivery, but in design-led, UX-rich product development — especially for consumer-facing digital work — some of its peers may stand out more.
  • Multitiered project structure and distributed delivery risk: With TCS frequently managing large, multitiered projects involving several layers of management and globally distributed technical teams, there's a risk of knowledge loss and technical debt.


• Thoughtworks - Visionary
  

  Pros:

  • Thought leadership and industry influence: Thoughtworks' legacy in agile, microservices, and data mesh is reinforced by ongoing 'thought capital' in areas such as platform engineering, responsible AI, and sustainable delivery.
  • Strategic shift to industry depth: Thoughtworks is pivoting from a purely technology-first, industry-agnostic model to one with industry focus.
  • Differentiated, high-value partnerships and ecosystem play: Thoughtworks is crafting unique, high-value partnerships (e.g., NVIDIA for model post-training, Mechanical Orchard for mainframe modernization).

  Cons:

  • Leadership and market flux: Thoughtworks is in the midst of a sweeping transformation — new leadership, new offerings, new commercial models, and a recent privatization.
  • Outcome-based contracts: Despite Thoughtworks' emphasis on business value and transformation, only 4% of its CSD revenue currently comes from outcome-based contracts.
  • Concerns about overall viability: Thoughtworks has experienced declines in CSD services revenue (-11%) and FTEs (-5%).


• Virtusa - Niche Player
  

  Pros:

  • Strong industry-focused engineering: Virtusa's 'domain-driven engineering' integrates reusable industry components and GenAI, with particular strength in banking, financial services, and insurance.
  • Advanced modernization and platform development: Virtusa reliably delivers complex engineering projects, especially in application and legacy modernization, with proven cost and time benefits.
  • Flexible global engagement and talent models: Virtusa provides commercial flexibility, with 54% of deals structured as T&M and 46% as fixed-price.

  Cons:

  • Demonstrated innovation: Virtusa demonstrates solid technical execution and is investing in new technologies and IP, but evidence of disruptive or transformative innovation remains light.
  • Narrow vertical focus: With 60% of sales concentrated in banking and a continued reliance on existing clients, there is a risk of long-term viability if market conditions change.
  • Technology-centric services: Virtusa's case studies reflect competent technology delivery, though the depth of customer context and vertical alignment could be strengthened.


• Wipro - Challenger
  

  Pros:

  • AI-led transformation at scale: Wipro embeds AI across the SDLC, deploying over 1,500 use cases and more than 200 AI agents, with dedicated AI leaders in client accounts.
  • Enterprise-grade delivery and platform engineering: Wipro's global delivery model and industry-aligned teams enable the execution of large, complex transformation programs.
  • Disciplined talent development and industry alignment: Fifty percent of Wipro's engineering workforce has completed advanced AI training, supported by partnerships with leading institutions.

  Cons:

  • Concentration on existing client base: Wipro's CSD revenue is heavily reliant on existing clients, with only 2.5% coming from net-new logos.
  • Evolving business value narrative: Wipro's CSD services excel in technical delivery and AI-driven productivity, but its consulting-led transformation capabilities are still developing.
  • Lower investments in reskilling/IP creation: Wipro's CSD invests a lower share of revenue in reskilling and new asset/IP creation compared with the group average.

Reference

• Gartner, Magic Quadrant for Custom Software Development Services, 01-Dec-2025, ID G00827209

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