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Service 05 of 07 · AI Infrastructure Layer
Execution Services

The AI stack.
Live before the first sprint.

Your core AI development stack deployed, configured, and end-to-end tested before your team arrives. Your engineers start building on day one — not spending the first week configuring tools.

AI Platform & Tooling — Service Overview
05
Service Details
Service
05 of 07 · AI Infrastructure Layer
Follows
Infrastructure and IT Setup
Duration
2 to 4 weeks (parallel to IT)
Output
Full AI stack live and tested
Service Progress
01 GCC Strategy & Design
02 Legal and Compliance Setup
03 Talent Acquisition
04 Infrastructure and IT Setup
05 AI Platform and Tooling ← You are here
06 Operations Management
07 GCC Scaling and Optimization
AI toolchain operational before sprint one

What This Service Delivers

Your AI stack configured
and tested before you start.

The difference between an AI team that ships on day one and an AI team that spends two weeks configuring tools is entirely in how the platform is set up before they arrive. We deploy your complete AI development stack and run a test sprint before your first team member starts.

🤖

AI Development Stack

Core AI development environment — model training infrastructure, experiment tracking (MLflow, Weights and Biases, or equivalent), vector databases, and inference endpoints — configured to your specifications.

Agentic Workflow Infrastructure

For teams deploying agentic AI systems — n8n, LangGraph, or custom orchestration infrastructure configured to your architecture. API gateway, rate limiting, and cost controls in place from the start.

🔬

MLOps Pipeline Setup

CI/CD for ML — model versioning, testing, deployment pipelines, and monitoring infrastructure. Your model development workflow from experiment to production, configured and tested.

☁️

Cloud and Compute Configuration

Cloud accounts (AWS, GCP, Azure) configured to your standards. GPU compute provisioned and cost controls in place. Data storage, access controls, and backup policies established.

📊

Collaboration and Knowledge Stack

Slack, Jira, Confluence, GitHub or equivalent — configured to match your global team’s workflow. The India team is integrated into your existing tools from day one.

The Process

The process. Every step defined.

01

AI Stack Specification

Based on your domain and team architecture — which models, which frameworks, which MLOps tools, which cloud provider. Confirmed before any provisioning begins.

Week 1

02

Cloud and Compute Provisioning

Cloud accounts configured. GPU instances provisioned. Storage, networking, and access controls established. Cost budgets and alerts set before anyone starts running experiments.

Week 2

03

AI Toolchain Deployment

Experiment tracking, model registry, inference infrastructure, vector databases — all deployed and configured. API keys, access credentials, and integration with the development environment.

Week 2-3

04

Agentic Infrastructure Setup

Orchestration framework, API gateway, and workflow tooling deployed for teams building agentic systems. Integration with the model serving layer tested end-to-end.

Week 3

05

Test Sprint

A full test sprint run before the team arrives. Data ingested. Experiments logged. A model trained and deployed through the full pipeline. Everything confirmed working before day one.

Week 4 — before team starts

The Full Execution Stack

The other services
in the stack.

AI platform built for your stack

Talk to a GCC architect about your AI toolchain requirements. We’ll spec the stack before you commit.

Service Details

Service

05 of 07

Duration

2 to 4 weeks (parallel to IT)

Output

Full AI stack live and tested

Next

Operations Management

AI Platform & Tooling

The AI stack your team
needs to ship from day one.

AI Platform and Tooling is deployed in parallel with Infrastructure and IT Setup — both live before your team arrives.