Coforge Launches AI Launchpad to Help Enterprises Build and Run AI Stacks In-House

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Coforge unveiled AI Launchpad, an enterprise AI platform that enables organizations to build, deploy and operate their own AI stacks within controlled environments. Powered by Coforge Nuuron, the offering addresses challenges around data sovereignty, cost governance and vendor lock-in while helping move AI projects from pilots to production.

Coforge Introduces Platform for Self-Owned Enterprise AI Infrastructure

Coforge has launched AI Launchpad, a comprehensive enterprise AI offering designed to help organizations build and run AI stacks entirely within their own controlled environments

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. The platform, powered by Coforge Nuuron, enables enterprises to build, fine-tune, deploy and operate their own AI infrastructure while maintaining full ownership of data, intellectual property and AI environments. This launch addresses a critical shift in enterprise AI adoption, where organizations increasingly demand greater control over their AI capabilities rather than relying solely on third-party providers.

Tackling the Journey from Pilot to Production

Despite open-weight AI models gaining mainstream adoption, many organizations struggle to move AI projects from experimental pilots to full production environments

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. The challenges include talent shortages, fragmented infrastructure, and stringent governance and auditability requirements. AI Launchpad was specifically designed to overcome these barriers through an integrated platform and managed services approach. The offering allows enterprises to route workloads across open-weight AI ecosystem models and frontier AI models based on business requirements, regulatory constraints, performance needs and cost considerations

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. This flexibility reduces dependence on any single model or technology provider, effectively eliminating vendor lock-in concerns.

Six Integrated Services for Complete AI Stack Management

Coforge AI Launchpad delivers a comprehensive suite of six integrated services that cover the entire AI lifecycle

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. These include Strategy and Advisory, Infrastructure and Platform, Model Engineering and Customization, Deployment and Integration, LLMOps, Observability and Guardrails, and Governance, FinOps and Managed Run services. This integrated approach provides enterprises with end-to-end capabilities for managing their AI infrastructure without requiring extensive in-house expertise. The platform's LLMOps capabilities ensure continuous monitoring and optimization of AI models in production, while FinOps services help organizations maintain cost governance across their AI operations.

Real-World Deployments Show Immediate Impact

Coforge is already implementing AI Launchpad with clients operating in sectors where data sovereignty and regulatory compliance are business-critical

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. Current deployments include a sovereign AI environment for a US healthcare intelligence company, addressing the sector's stringent data privacy and compliance requirements

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. Additionally, managed AI routing helped a major US bank reduce AI-related costs while maintaining governance and auditability standards. These early implementations demonstrate the platform's ability to deliver tangible benefits in highly regulated industries where control over AI infrastructure is non-negotiable.

The Shift from Renting to Owning Intelligence

"Enterprise AI is entering a new phase where control matters as much as capability," said Lalit Wadhwa, Chief Technology Officer at Coforge

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. Anup Nair, Chief AI Commercial Officer at Coforge, emphasized this transformation: "Enterprises spent the first wave of AI renting intelligence. The next wave will be about owning it"

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. This perspective highlights a fundamental shift in how organizations approach AI deployment. Rather than building critical capabilities inside environments they don't fully control, enterprises can now leverage AI Launchpad to create AI systems on their own terms while retaining the flexibility to evolve as their business requirements change. The platform gives organizations transparency, flexibility and governance needed to adapt their AI strategies as the technology landscape evolves, positioning them to respond quickly to emerging opportunities and regulatory requirements.

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