Azure AI Foundry Corporate Brochure

Ready

Prepixo AI Academy

Build Production-Ready AI Systems in 5 Days

Hands-on Azure AI Foundry Program for enterprise engineering teams, solution architects, and technical leaders. Designed to convert AI intent into deployable systems with architecture, integration, RAG, governance, and capstone execution.

Real Use Cases Capstone Project 15-Day Sandbox Access
5 Days

Accelerated implementation track

2-5 Participants

Focused cohort for practical mentoring

Production Focus

Build, deploy, and integrate real systems

Sandbox Access

Continue practice for 15 days post program

Pilot AI Build + Integrate Production

Problem vs Solution

Why AI Initiatives Fail and What This Program Fixes

Many AI efforts remain trapped in pilots because teams lack an executable architecture, integration readiness, and governance discipline. This program aligns technical depth with practical delivery so teams can move from concept to production with confidence.

Why AI Initiatives Fail

  • Stuck in POC stage
  • No production architecture
  • Integration challenges with backend systems
  • Cost and governance issues

What This Program Changes

  • Move from experimentation to production systems
  • Build real applications using enterprise patterns
  • Integrate AI with APIs, services, and data
  • Apply governance and safety controls from day one

Problem-to-Value Transition

Illustrative
Pilots initiated94%
Integrated pilots58%
Production-ready architecture35%
Scaled production systems18%
Pilot Bottlenecks Production Enablement

Program Journey

5-Day Accelerated Journey with Day-wise Execution Points

The journey compresses a typical 10-day breadth into a focused 5-day implementation sprint. Each day combines concept clarity, guided labs, and practical output checkpoints.

Day 1 - Introduction, Architecture, Setup

  • Overview of Azure AI ecosystem and Foundry concepts
  • Architecture patterns for AI applications
  • Environment setup and prerequisites

Day 2 - Model Catalog, Deployments, Scaling

  • Exploring model catalog: OpenAI, Phi, Llama
  • Deployment configurations and endpoints
  • Scaling considerations and quotas
  • Prompt engineering fundamentals and few-shot patterns

Day 3 - Advanced Prompting, Evaluation, Guardrails

  • Prompt optimization techniques
  • Output evaluation and tuning loops
  • Guardrails and safety mechanisms
  • Tools, agents, and flow orchestration

Day 4 - RAG, Search, Vector Stores, App Build

  • RAG fundamentals and enterprise grounding patterns
  • Azure AI Search integration
  • Embeddings and vector database concepts
  • Building end-to-end AI applications in Azure AI Studio

Day 5 - Integration, Governance, Capstone

  • API integration with backend services (Python/JS)
  • Security, responsible AI, monitoring, compliance
  • Capstone project build, presentation, and review

Topic Density by Day

Illustrative
Day 148
Day 269
Day 378
Day 484
Day 590
1 2 3 4 5

Architecture Diagram

Reference Layered Architecture for Production AI Systems

The design separates user interaction, service orchestration, model execution, retrieval layers, and enterprise data sources so teams can scale without compromising governance, security, and maintainability.

User / Application Layer
API / Backend Layer
Azure AI Models Layer
RAG Layer (Search + Vector Database)
Enterprise Data Sources
  • Centralized prompt and policy controls across workloads.
  • Grounded responses using enterprise data and retrieval logic.
  • Backend integration enables observability, audit, and traceability.
  • Security and access control enforced through service boundaries.

Use Cases

Enterprise Use Cases and Expected Impact

Training outcomes are tied to practical implementation patterns. Teams practice use-case mapping, design choices, and performance tradeoffs while building deployable workflows.

Document Intelligence

RAG-based document understanding and extraction.

Enterprise Chatbot

Internal knowledge assistant with policy-aware responses.

AI Search

Semantic retrieval across enterprise information sources.

Workflow Automation

AI-driven process acceleration and decision support.

Impact Matrix

Illustrative
Use CaseSpeedAccuracyAdoptionOps Efficiency
Document Intelligence84887582
Enterprise Chatbot79818773
AI Search86838085
Workflow Automation82777290

Delivery Model

How the Program Is Delivered and Why It Works

The model combines instructor-led guidance with constrained cohort size to maximize practical depth and direct mentoring. This avoids passive training and drives measurable implementation confidence.

Delivery Details

  • Instructor-led sessions
  • Small batch: 2-5 participants
  • Live hands-on labs
  • Customization for enterprise use cases

15-Day Sandbox Access

  • Continue building after classroom sessions
  • No additional infrastructure setup required
  • Apply skills on realistic scenarios
  • Reinforce retention through applied execution

Model Comparison

Illustrative
DimensionPrepixo ModelTypical Self-paced
Guided Hands-on Hours329
Mentor SupportHighLimited
Post-training Practice Window15 days0-2 days

Outcomes

Before vs After Transformation

The program is designed for capability shift, not concept coverage alone. Teams exit with a practical foundation to design, deploy, and govern enterprise AI systems in production environments.

Before

  • AI concepts only
  • No deployment experience
  • Fragmented understanding
  • Low confidence in integration decisions

After

  • Build real AI applications
  • Deploy production systems
  • Integrate AI with backend services
  • Apply governance and responsible AI practices

Capability Delta

Illustrative
Architecture readiness+52
Deployment confidence+58
Integration maturity+60
Governance alignment+49

Commercials and CTA

Turn Your AI Strategy Into Working Systems

If your team is expected to deliver AI outcomes in production, this program provides an implementation path that aligns skills with architecture, integration, and governance priorities.

5-Day Program

INR 48,000 per participant (inclusive of 18% GST)

10-Day Program

INR 74,000 per participant (inclusive of 18% GST)

  • Includes instructor-led classroom training, labs, and learning material.
  • Batch size: 2-5 participants.
  • Program can be aligned to your enterprise use case context.
Share your use case. Get a customized training plan.

Contact: +91-8123963413