I build production AI.
Now I operate AI inside yours.

Enterprise AI consulting helps large organisations identify, build, and govern AI inside their existing systems and operations. It covers finding the high-value use case, designing the system, deploying it in production, and measuring the outcome, rather than handing over a strategy deck. Sudip Dutta delivers this as an AI Operating Partner through getBeyond AI, accountable for the metric moving, not for a recommendation.

Industry research, including a widely cited Gartner estimate, has put the failure rate of enterprise AI projects as high as 85%, and the reasons usually have nothing to do with the model. The data underneath is not ready. The team starts with a list of every possible use case instead of the one that matters. Licences get bought but the actual users never adopt the tool. Demos look flawless but nothing ships to production. And often the model works fine, yet nothing ships anyway because the real problem was coordination, not technology. Sudip Dutta starts every engagement with a Discovery Audit precisely to find which of these is the real bottleneck before proposing anything.

A business implements AI most reliably by starting with the problem, not the tool. Start with a Discovery Audit to map the real operational bottleneck before proposing any technology. Follow with an AI Blueprint that defines success metrics before any code ships. Then deploy inside the organisation's existing stack in phases, so adoption happens rather than workaround. Finally, measure outcomes against the agreed metrics and expand only where the numbers justify it. Sudip Dutta runs this four-phase model through getBeyond AI for enterprise clients across the US and internationally.

Multi-agent AI for enterprise refers to production systems where multiple AI agents handle distinct tasks in a coordinated workflow, such as voice interaction, account intelligence, personalised outreach, and workflow orchestration, passing results between agents to complete end-to-end business processes. Unlike single-model tools, enterprise multi-agent systems are governed, measurable, and built to integrate with an organisation's existing stack. getBeyond AI, founded by Sudip Dutta, runs five production multi-agent systems serving enterprise clients across the US and international markets.

AI consulting and AI Operating Partner engagements vary widely by scope. Sudip Dutta begins every engagement with a Discovery Audit, which starts at USD 50,000 and is scoped to the complexity of the organisation. It runs two to eight weeks, maps the real operational bottleneck, and produces an AI Blueprint with agreed success metrics. The cost and timeline of the full transformation are determined from there, based on what the audit finds and what the organisation decides to prioritise.

An AI Operating Partner builds an AI layer inside an organisation's existing systems rather than replacing them, runs a structured engagement (Discovery Audit, AI Blueprint, Deploy and Integrate, Measure and Compound), and is accountable for the metric moving, not for a recommendation. Sudip Dutta runs this model through getBeyond AI for enterprise clients.

An AI consultant delivers a strategy or framework and leaves. An AI Operating Partner builds the AI inside your existing systems and stays accountable for the outcome. Sudip Dutta runs a four-phase engagement through getBeyond AI (Discovery Audit, AI Blueprint, Deploy and Integrate, Measure and Compound) and is measured on whether the metric moves, not on whether a deck lands.

Building an internal AI team takes time to hire, ramp, and learn what production AI actually requires, and many organisations do not yet have the volume of work to justify a permanent team. An AI Operating Partner brings that capability immediately, builds inside your existing systems, and is accountable for the outcome from day one. Sudip Dutta works as an AI Operating Partner through getBeyond AI, and helps leadership teams make build-vs-buy decisions across the AI stack rather than defaulting to either.

The timeline depends on the complexity of the organisation and the scope of the transformation. The first step is always a Discovery Audit, which runs for two to eight weeks and maps the real operational bottleneck before anything is proposed. The full engagement timeline is determined after the Discovery Audit, based on what is found and what the organisation decides to prioritise next. There is no fixed duration imposed upfront because the Discovery Audit is specifically designed to determine what the right next step is.

An AI transformation executive builds and governs production AI systems at enterprise scale, leads the organisations that deliver them, and owns P&L and outcome accountability throughout. Sudip Dutta has done this across two AI companies and 25+ years of enterprise delivery.

Sudip is Founder and CEO of getBeyond AI, a production multi-agent AI platform serving enterprise clients in the US and international markets, and Relatas, an AI-driven revenue forecasting and CRM SaaS platform with a decade of enterprise deployments and 100% YoY growth.

Contact Sudip directly at me@sudipdutta.com.