I build production AI.
Now I build it 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.

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 (2 to 8 weeks) to map the real operational bottleneck before proposing any technology. Follow with an AI Blueprint (2 to 8 weeks) that defines success metrics before any code ships. Then deploy inside the organisation's existing stack in phases (typically 6 to 18 months), 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: a fixed fee, scoped to the organisation after a first call. It runs 2 to 8 weeks and maps the real operational bottleneck, then leads into an AI Blueprint (2 to 8 weeks) with agreed success metrics. Implementation is scoped from there and typically runs 6 to 18 months.

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 2 to 8 weeks and maps the real operational bottleneck before anything is proposed, followed by an AI Blueprint of 2 to 8 weeks. Implementation typically runs 6 to 18 months, depending on what the audit finds and what the organisation decides to prioritise.

An enterprise AI consultant finds where AI will move a business metric, designs the system, and gets it into production inside the systems the company already runs. Sudip Dutta does this hands-on as an AI Operating Partner through getBeyond AI, backed by 25+ years of enterprise sales and delivery and two AI companies built from scratch.

Sudip has built two AI companies. He is Founder and CEO of getBeyond AI, a production multi-agent AI platform serving enterprise clients in the US and international markets. He founded Relatas (2015 to 2025), an AI-driven revenue forecasting and CRM SaaS platform with a decade of enterprise deployments and 100% YoY growth for its first three years.

Through getBeyond AI, Sudip has built AI inside the existing systems of a publicly listed Indian company and a UK-based D2C brand, solving for distribution and D2C consumer businesses. Every engagement builds inside the systems the company already runs.

Sudip is based in Bengaluru, India, but is often on the road, working with companies across the US, the UK and India. Engagements mix on-site travel and remote work, depending on the company's location and the scope.

Contact Sudip directly at me@sudipdutta.com.