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Industries We Serve — AI Startups
AI GCC for
AI-Native.
Startups.
For AI-native companies that need to move fast, build deep, and own everything. Your India GCC gives you the AI engineering team to match your ambition — at a cost that extends your runway and a structure that compounds your IP permanently.
AI Startup GCC Profile
Full-Stack AI Capability
for AI-First Companies
3×
More engineers for the same burn rate as US hiring
65%
Cost saving vs equivalent US AI engineer
30d
Days to first sprint — AI Pod entry point
100%
IP ownership — critical for fundraising
- IP clean · Entity owned by you · Team scales with you
65%
Lower burn rate vs building your AI team in the US
3×
More AI engineers for the same monthly spend
$14K
Per month for a 3-person LLM Pod in Pune
100%
IP ownership — clean for due diligence and fundraising
Why India for AI Startups
Why AI startups are building
their engineering teams in India.
For an AI-native startup, the engineering team is the product. The speed at which you can build, experiment, and ship determines whether you win your market. India gives you the ability to triple the size of your AI engineering team for the same monthly burn — without sacrificing IP ownership, quality, or institutional permanence.
Unlike outsourcing (which creates IP fragmentation that kills due diligence), your India GCC team are your employees, their work is your IP, and the institutional knowledge they build is yours permanently. When you raise your Series B, your cap table does not include a vendor who owns your training data.
What Your GCC Builds
What AI startups build in India GCCs.
🧠
Foundation Model Development
Training and fine-tuning proprietary models — the core IP that differentiates AI-native companies from those using the same public APIs as every competitor.
→ LLM Engineers, Neural Network Engineers, AI Research Scientists
⚡
Inference Optimisation
Making your models fast and cheap enough to serve at scale — quantisation, distillation, speculative decoding, and custom serving infrastructure.
→ Neural Network Engineers, MLOps Engineers
🤖
Agentic Product Systems
The multi-step AI agents that are increasingly the product itself — complex, stateful, tool-using systems that go far beyond chatbot architecture.
→ AI Agent Developers, LLM Engineers
🔬
AI Research
Novel architectures, ablation studies, and frontier experiments — the research function that keeps you ahead of competitors who are deploying yesterday’s techniques.
→ AI Research Scientists, Neural Network Engineers
📊
Evaluation & Safety
Systematic evaluation frameworks, red teaming, and safety systems — the infrastructure that makes your AI product reliable enough to ship to production users.
→ Prompt Engineers, LLM Engineers
⚙️
ML Platform
The production infrastructure that keeps everything running — training pipelines, model serving, monitoring, and the CI/CD that lets your team ship fast.
→ MLOps Engineers, Platform Engineers
SGCC Team Profile
Your AI startup GCC team.
Core model capability — the product.
₹20–55 LPA
AI Agent Developers
Agentic product architecture — the UX.
₹15–50 LPA
MLOps Engineers
Production infrastructure — the reliability.
₹12–35 LPA
AI Research Scientists
Frontier capability — the moat.
₹20–80 LPA
Neural Network Engineers
Custom architectures — the differentiation.
₹15–45 LPA
- All team members are your employees. IP assigned to you before work begins. GCC Digital Twin maps the exact team before you hire anyone.
Common Questions
Questions about GCCs
for ai startups.
Is a GCC the right model for an early-stage AI startup?
The GCC model scales down to a 3-person AI Pod — operational in 21 to 30 days, from $8K per month all-in. The question is not whether you’re too early for a GCC. It’s whether you want the IP and the team to be permanently yours from the first day. The POD model gives you GCC ownership without GCC overhead.
How does the India GCC IP structure work for due diligence?
Every engineer is employed by your entity (or under a structure with direct IP assignment), and every IP assignment agreement is signed before work begins. Your cap table does not include the GCC operator, your models are not encumbered by vendor agreements, and your training data belongs to you. This is the clean IP structure that institutional investors want to see.
Can we move fast enough with a remote India team?
Yes — the GCC model integrates your India team into your existing engineering workflow. Same Jira, same GitHub, same Slack, same sprint cadences. The velocity advantage is significant: a 10-person India team running on your roadmap ships more than a 4-person US team at the same monthly burn.
What is the minimum size for an AI startup GCC?
3 people. An AI Pod of 3 engineers — 1 senior lead, 2 mid-level — is the entry point. It is a full, owned GCC: your employees, your IP, your entity. From $8K per month all-in. Most AI startups who start with a 3-person Pod scale to a 10-person team within 6 months.
Other Industries
Miracle Global builds GCCs
across industries.
🏥
Healthcare & Life Sciences
Health AI startups with clinical data considerations.architectures your team designs.
Prompt Engineers — Your GCC
Build your AI team in India.
Own everything. Ship fast.
Design your startup GCC. We’ll map your team, your IP structure, and your 30-day activation plan.