AI GCC · India

    Build and scale your AI GCC in India.

    NeoIntelli helps global companies design, build, operate and scale AI-led Global Capability Centers in India. From AI strategy and specialist talent to production AI engineering, delivery teams and GCC operations, one partner connects the complete capability lifecycle.

    Estimate GCC Cost
    • Strategy
    • Talent
    • AI Engineering
    • Delivery
    • Operations
    • BOT

    Flagship service

    AI GCC

    Build an India capability center designed around AI from day one.

    An AI GCC is designed backwards from the AI and data work it is meant to own. Strategy, specialist talent, data foundations, generative and agentic AI, MLOps, AI infrastructure and governance are set as one operating model rather than added to a delivery center afterwards.

    • AI strategy and the mandate the center owns
    • Specialist AI, data and platform talent
    • Data foundations, GenAI and Agentic AI in production
    • MLOps, AI infrastructure and AI governance
    • The operating model that holds it together

    What is an AI GCC?

    An AI GCC is a Global Capability Center designed around AI, data and engineering capability as part of its core operating model.

    It combines specialist talent, data and AI platforms, production engineering, model and agent operations, governance and enterprise ownership inside a dedicated capability center rather than treating AI as a separate innovation project.

    Build the team

    AI Talent

    Hire AI specialists your technical team does not need to screen from zero.

    Specialist sourcing across the AI and data disciplines, with NeoHireX carrying the screening and practicing AI engineers carrying the technical validation. Your engineers spend interview time choosing between credible candidates instead of filtering the pipeline.

    • GenAI and Agentic AI
    • Machine learning and data science
    • Data engineering
    • MLOps and AI platform
    • AI leadership and executive search

    How a shortlist is built

    1. 01Source
    2. 02NeoHireX screen
    3. 03AI first round
    4. 04Senior technical validation
    5. 05Qualified shortlist

    Build the AI

    AI Engineering

    Take AI from proof of value to production.

    AI prototypes are easy. Production AI is not. Getting there needs data, software engineering, integration, evaluation, observability, security, operations and unit economics treated as one engineering problem rather than a demo that has to be hardened later.

    • Generative and Agentic AI
    • Applied AI and machine learning
    • AI data engineering
    • AI product engineering
    • AI agents, automation and evaluation
    • MLOps, LLMOps and AgentOps

    AI prototypes are easy. Production AI is not.

    What separates the two is rarely the model. It is the data it runs on, the systems it integrates with, the evaluation that proves it works, the observability that catches it when it stops, the security and governance around it, and the cost per outcome once real traffic arrives.

    Deploy the team

    AI Delivery Teams

    Deploy an AI team that owns delivery.

    AI Talent is how you hire people. AI Delivery Teams is how you deploy execution capability: a senior-led team working inside your roadmap, repositories and release cadence, accountable for the outcome rather than for supplying CVs.

    • Work inside your roadmap and repositories
    • Senior-led, accountable for the delivered outcome
    • Scale the team up or down against the roadmap
    • A defined path to transferring the team to you

    Design & launch the center

    GCC Strategy & Setup

    Design the GCC around the mandate, not the headcount.

    A GCC is an ownership decision before it is a location decision. What the center is meant to own determines the operating model, the city, the workforce plan and the launch sequence, so the mandate is settled first and the build follows from it.

    • Business case and mandate
    • Operating model and governance design
    • Location strategy and workforce plan
    • Entity, workplace, IT and launch
    • Modernization of an existing center

    A GCC is an ownership decision before it is a location decision.

    Deciding what the center owns settles almost everything downstream: which roles you hire, which city can supply them, how the work is governed, and whether the end state is a managed center or a captive one.

    Run & scale the center

    GCC Operations

    Operate the local GCC systems while your leadership owns the mandate.

    The local operating layer runs day to day: people and HR, workforce, workplace and IT, service management, performance, governance and compliance coordination. Your leadership keeps the mandate and the delivery agenda.

    • People, HR and workforce operations
    • Workplace, IT and security
    • Service management and performance
    • Governance and compliance coordination
    • BOT, transition and scale

    An optional ownership path

    1. 01Managed
    2. 02Stabilize
    3. 03Scale
    4. 04BOT
    5. 05Captive

    Not every center follows this sequence. It exists so that a managed start does not close off captive ownership later.

    Choose your GCC starting point

    Where are you in the GCC journey?

    Start smaller

    AI Micro GCC

    One focused India team, built and validated first, with room to grow into a larger center.

    • Startups and scale-ups
    • Mid-market
    • A first India capability
    Start with AI Micro GCC

    Build a new center

    AI GCC

    A capability center designed around AI, data and engineering from the first business case onward.

    • Strategic AI, data and engineering capability
    • A larger mandate
    • Long-term enterprise ownership
    Plan My AI GCC

    Transform an existing center

    GCC Modernization

    Move an existing center to a higher-value mandate with AI, data and product ownership inside it.

    • An existing GCC
    • AI transformation
    • Product and platform ownership
    Modernize My GCC

    Why NeoIntelli

    One operating partner across the AI GCC lifecycle.

    What connecting those layers actually changes

    • Senior involvement in the decisions that set the model, not only at the pitch
    • AI and data specialization rather than general offshore delivery
    • NeoHireX-supported hiring with practitioner-led technical validation
    • Production AI engineering capability, not advisory alone
    • AI delivery teams that own outcomes inside your cadence
    • The option to start with an AI Micro GCC and grow from there
    • Integrated GCC operations rather than a hand-off to a third party
    • Capability transfer designed in, including a BOT path to captive ownership

    How we engage

    Design, build, operate, then scale or transfer.

    A defined engagement model, so you always know which phase you are in, what it has to produce, and what comes next.

    01

    Design

    • Mandate
    • Business case
    • Operating model
    • Location
    • Roadmap
    02

    Build

    • Talent
    • Leadership
    • AI engineering
    • Entity and workplace
    • Platform and infrastructure
    03

    Operate

    • People
    • IT
    • Service management
    • Governance
    • Performance
    04

    Scale or Transfer

    • New capability
    • AI transformation
    • Leadership
    • BOT
    • Captive ownership

    AI GCC questions

    AI GCC questions, answered.

    What is an AI GCC?

    An AI GCC is a Global Capability Center designed around AI, data and engineering capability as part of its core operating model. It combines specialist talent, data and AI platforms, production engineering, model and agent operations, governance and enterprise ownership inside a dedicated capability center, rather than treating AI as a separate innovation project bolted onto a delivery center.

    How is an AI GCC different from a traditional GCC?

    A traditional GCC is designed around delivering defined work at scale, and is measured on capacity and cost. An AI GCC is designed around changing how that work is done. Data engineering and model or agent operations are core roles rather than support roles, AI infrastructure is part of the design, and governance has to cover models and agents as well as software.

    Why build an AI GCC in India?

    India offers depth across the specific disciplines an AI GCC needs together in one place: AI and machine learning engineering, data engineering, MLOps and platform work, plus the broader software engineering around them. That depth, combined with an established GCC operating environment and workable overlap with US and European hours, is why most global companies evaluate India first for AI capability centers.

    What is an AI Micro GCC?

    An AI Micro GCC is a small, dedicated India AI engineering capability that starts with one focused team instead of a full center. It gives you a validated team, your own IP and a working operating model without the overhead of a large traditional GCC, and it is designed so the same structure can expand into a full AI GCC when the business case supports it.

    How much does an India GCC cost?

    It depends on the roles, seniority mix, headcount and city, so a single figure is misleading. The GCC Cost Calculator models those variables and returns a fully loaded monthly and annual operating estimate, including the employer costs that salary benchmarks usually leave out. Use it to size a first team or to build the cost case for a full center.

    Can we start with a small India team and scale later?

    Yes. Starting with an AI Micro GCC or a single AI delivery team is a common entry point. The point of starting small is to validate the model, the roles and the working rhythm before committing to a larger structure. Designing the operating model properly at the start is what makes the later expansion an extension rather than a rebuild.

    Can a managed GCC eventually become fully captive?

    Yes, through a Build-Operate-Transfer path. NeoIntelli can build and operate the center first, then progressively transfer employment, systems, governance and leadership to your own India entity once agreed readiness conditions are met. Not every company wants captive ownership, so the path is optional, but a managed start should never close it off.

    Build your India AI capability

    Start with one team. Scale into an AI GCC.

    Whether you are testing the India model with an initial AI squad or designing a full capability center, NeoIntelli can help define the right starting model and build the operating path around it.