You're a SaaS AI start-up. You've raised and in
growth stage.
It's time to build your capability
centre in India.
What leading SaaS companies are building in India
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Builds AI/ML, data science & product engineering for global platforms
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Develops AI revenue forecasting & pipeline intelligence platform
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R&D center accelerating AI/ML platform innovation
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Technology center for DevOps, security, and platform engineering
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Global product engineering for AI-powered reputation platform
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R&D hub for Experience Cloud & Creative Cloud
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Assists product development and customer operations
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Builds cloud-native data protection & backup platform
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Engineers and maintains AutoCAD, Fusion 360 & AEC product suite
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Develops AI-powered contract lifecycle management platform
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Builds AI-driven workflow automation for enterprise customers
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Builds AI engineering for CRM & customer platform
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AI R&D hub processing and computer vision & agentic AI
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Builds core HR, IT & Finance platform modules
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Building AI, cloud, & data science supporting the Payments platform
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Develops AEC & geospatial SaaS for global construction
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Drives R&D & ML for B2B intelligence platform operations & product support
Why SaaS companies prefer India to set up Global Capability Centres (GCC)
400K AI Engineers in India today. 700K by 2027.
40 - 60% cost advantage - significant savings versus equivalent US-based teams.
350+ SaaS GCCs already operate in India.
Government incentives - Real estate, talent, opex & capex benefits supported by policy.
People Equation
Credentials
We help SaaS companies do two things
- → Set up an India Capability Centre without losing control of product or IP.
- → Get real AI into your product through a fractional AI pod.
Nano GCCs
A Nano GCC is a fully owned 50-100 person capability team in India,
built as a direct extension of your company.
Designed for SaaS companies
that need to scale without losing control of product, culture or IP.
- → Costs are ~40% of the US, with a 50-person team running under $2M all-in.
- → The speed to start is measured in weeks.
- → 350+ SaaS GCCs already operating in India.
- → And you're hiring from depth: 75,000+ SaaS developers, with the talent pool still expanding.
Three ways to start; Pick your depth.
Start light, scale when it makes sense. Every model gives you direct control from day one.
Build teams in India before a legal entity
Most efficient way to scale quickly in India.
- No Entity Required
- No compliance commitments upfront
- Ideal for up to ~30 team size
What you get
- First hire in 2 weeks
- PE runs all enabling functions
- Retain your IP & Culture
- Time to design your long-term org structure before committing
Not a fit when
- You plan to cross 150 people in India
- Customer or security contracts need the team on your payroll
We build it. You own it.
Ideal for 50+ team size and beyond. India as a long-term capability base.
What you get
- India entity live in 3 months
- Team shipping work in 3 to 4 months
- We run HR, Finance, IT during operate
- Clean transfer when you want
- We handle tax, compliance, transfer pricing, audits
Not a fit when
- You are still testing the India bet
- You need a team in under 4 weeks
Your org and employee essential services are managed by an ecosystem of experts
Experienced functional leaders manage your India operations end-to-end. Ideal for large multi-year programs.
What you get
- Operational in 8–12 weeks.
- Hire-to-retire lifecycle managed by PE
- Structured processes, governance, and ecosystem in place
- Single partner across functions
Not a fit when
- The work is core product IP you want shaped in-house
- The engagement is small. You will pay for overhead you do not need.
Fractional-AI Pods
Ship Production AI, embedded in your product.
AI is no longer a feature. It's the product. Growth-stage SaaS companies have a backlog of AI ideas, maybe a prototype or two, but nothing in production that moves revenue, NRR, or support metrics.
- → You can't justify a full AI team yet, and you can't wait 18 months either.
- → The AI Pod is a dedicated 3–5 person engineering team ( ML engineer, full-stack developer, product lead ) embedded in your workflow, shipping into your codebase.
What We
Actually Build
AI Lifecycle Engineering
Evaluation harnesses before the model. Drift detection after. CI/CD for ML. The infrastructure that keeps AI working at 3 AM, not just at demo time.
AI Governance & Compliance
Risk tiers, model cards, bias checks, audit trails. Built for HIPAA, SOC 2, and regulated environments; by design, not retrofit.
Agentic AI
RAG with contextual retrieval and re-ranking. Multi-agent orchestration with graceful failure. Model routing and token economics. Shipped, not theorized.
AI Decision Frameworks
Structured answers to “should we build this with AI?” Impact × feasibility × risk. Build-vs-buy evaluation. Every sprint starts with the right problem.
Production API Operations
Self-hosted model serving on your tenant. PII redaction at the gateway. Cost-routing logic that eliminates the 2–3× inference overspend most product teams accumulate as they scale.
and dives into your production codebase, not a PoC.
AI Sprint
AI Pod
AI Centre of Excellence (CoE)
Built by Engineers, Not Consultants
The people designing your system are the ones building it.
- Former AI CoE Head at a Fortune 500 FMCG
- Ex-VP Engineering at a US technology firm
- Lead AI engineer at a US technology firm
- Co-founded a company acquired by a Big 4 firm
Readiness Check
Are you ready for a
Nano-GCC
in India?
A Nano-GCC is your own dedicated team in India, not a vendor, not freelancers.
People who work only for you, built and managed end-to-end by People Equation.
