Azure OpenAI Service · Generative AI India

Deploy GPT-4o on
Your Enterprise Data

Azure OpenAI Service provides GPT-4o, GPT-4 Turbo, DALL-E 3, Whisper, and embedding models — hosted entirely within Microsoft's enterprise-grade, compliant Azure infrastructure. SchwettmannTech builds production Retrieval-Augmented Generation (RAG) systems, custom Copilot assistants, document automation, and code generation tools for Indian enterprises — with all data staying in Azure India regions under your control.

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Azure OpenAI Certified Partner India

GPT-4o · DALL-E 3 · Whisper Deployed

100% Data in Your Azure Tenant

GPT-4o

Latest model — multimodal, 128K context

100%

Data stays in your Azure tenant

RAG

On your private documents & Dataverse

PTU

Provisioned throughput for SLA guarantees

Azure OpenAI · GPT-4o Deployment Dashboard

Live

140K

Tokens/Day

↑ PTU Reserved

99.9%

Uptime SLA

↑ Guaranteed

18ms

P50 Latency

↓ Optimised

₹0

Data Egress

✓ India Region

RAG Pipeline — SharePoint + Dataverse

12,400 docs indexed · Azure AI Search · GPT-4o

Live

Custom Copilot — D365 Sales Assistant

Deal coaching · Email drafting · CRM data grounded

Active

Document Automation — Contract Review

128K context · Obligation extraction · Risk flags

Running

DALL-E 3 — Product Image Generation

250 SKUs/day · Brand guidelines applied · Auto-resize

Active

Azure OpenAI: GPT-4o processed 4,200 contract pages this week — extracting 847 obligations, flagging 23 risk clauses, and generating executive summaries in under 30 seconds per document. PTU reservation ensures consistent performance at peak loads.

GPT-4o

Multimodal Model with 128K Context Window

100%

Data Privacy — Never Used for OpenAI Training

PTU

Provisioned Throughput for Predictable Latency

RAG

On Your Private Docs, SharePoint & Dataverse

GPT-4o DeploymentRAG PipelinesDALL-E 3Whisper STTAzure EmbeddingsCustom Copilot AssistantsDocument AutomationFine-tuning GPT-3.5Semantic KernelLangChain AzureProvisioned ThroughputContent FilteringGPT-4o DeploymentRAG PipelinesDALL-E 3Whisper STTAzure EmbeddingsCustom Copilot AssistantsDocument AutomationFine-tuning GPT-3.5Semantic KernelLangChain AzureProvisioned ThroughputContent Filtering

Services

End-to-End Azure OpenAI Service Implementation

From RAG architecture design to production deployment and monitoring — our Azure OpenAI engineers build generative AI that works reliably at enterprise scale in India.

RAG on Enterprise Data

Build Retrieval-Augmented Generation systems on your proprietary documents — SharePoint libraries, Dataverse records, SQL databases, and Azure Blob Storage. Employees query company knowledge in natural language; GPT-4o answers are grounded in your data, not hallucinations. Azure AI Search provides hybrid vector + keyword retrieval for maximum answer accuracy.

GPT-4o · Azure AI Search · Hybrid RAG · SharePoint · Dataverse

Custom Copilot Assistants

Design and deploy branded AI assistants for sales, HR, finance, legal, and customer service using Azure OpenAI + Semantic Kernel + Azure AI Search. Deploy as a Microsoft Teams tab, web chat widget embedded in your portal, or as a D365 embedded panel — with role-based access controlling which data each user can query.

Custom Copilot · Teams · D365 · Semantic Kernel · RBAC

Document Automation

GPT-4o's 128K context window processes entire contracts, RFPs, financial reports, and regulatory filings. Extract obligations, identify risks, compare document versions, and generate executive summaries — at scale, in seconds. Approved for use in legal review, procurement, and financial analysis workflows.

Document Review · Contract Analysis · Obligation Extraction · 128K Context

Fine-tuning & PTU

Fine-tune GPT-3.5 on your domain-specific data — legal, medical, manufacturing, financial — for improved accuracy on specialised tasks. Provisioned Throughput Units (PTU) guarantee consistent sub-50ms latency SLAs for production applications where response time predictability is critical.

Fine-tuning · PTU · Domain AI · Latency SLA · Production Grade

DALL-E 3 & Multimodal

Generate product images, marketing visuals, architectural mockups, infographics, and training materials at scale using DALL-E 3. GPT-4o Vision analyses uploaded images, documents, and diagrams — enabling multimodal workflows for quality inspection, document understanding, and visual data extraction.

DALL-E 3 · GPT-4o Vision · Product Images · Multimodal

Enterprise Governance & Safety

All Azure OpenAI deployments in India regions — your data never leaves your tenant and is never used for OpenAI model training. Azure RBAC, managed identities, private endpoints, and content filtering layers ensure enterprise security. Full audit logging for DPDP Act and CERT-In compliance.

Data Privacy · DPDP Act · Private Endpoints · Content Filtering · CERT-In

Capabilities

Complete Capability Coverage

Our certified team covers every facet of this service — from strategy and implementation to managed operations and continuous optimisation.

RAG

Enterprise RAG Architecture

Our RAG architecture uses Azure OpenAI embeddings + Azure AI Search hybrid retrieval + GPT-4o generation — with semantic ranking and answer faithfulness evaluation to ensure accuracy before deployment.

Azure AI Search Hybrid Index
OpenAI text-embedding-3-large
Semantic Ranking Layer
Answer Faithfulness Eval

Copilot

Copilot Studio Integration

Azure OpenAI integrates natively with Microsoft Copilot Studio — allowing you to build custom AI assistants that deploy to Teams, web portals, and Dynamics 365 without managing infrastructure.

Copilot Studio Connector
Teams Deployment
D365 Embedded
No Infra to Manage

Privacy

India Data Residency

Azure OpenAI in India regions (Sweden, UK, East US available; India-hosted availability per Microsoft roadmap). All vector indexes in Azure AI Search deployed in Azure India regions — full data residency for DPDP Act compliance.

Performance

PTU & Throughput

Provisioned Throughput Units reserve model capacity for your exclusive use — eliminating noisy-neighbour latency. Production applications serving thousands of concurrent users achieve consistent sub-50ms response times.

Dev

Semantic Kernel & LangChain

We build Azure OpenAI solutions using Microsoft Semantic Kernel (C#/Python) and LangChain Azure — enabling complex agentic workflows, tool use, memory management, and multi-step reasoning chains.

Monitoring

LLM Observability

Azure Monitor + Application Insights tracks every GPT-4o call: token usage, latency, content filter events, and answer quality scores. Custom dashboards expose cost-per-conversation and accuracy trends for continuous improvement.

MLOps

LLMOps for Production

Prompt versioning, A/B evaluation, canary deployment of new model versions, and automated regression testing ensure your Azure OpenAI application improves continuously without production disruption.

Delivery

Our Azure OpenAI Delivery Framework

A proven 4-phase process from use case definition to production deployment — typically 4–8 weeks for most enterprise RAG and Copilot projects.

Phase 1 — Week 1

Use Case Definition & Architecture Design

Define RAG vs fine-tune vs direct generation

Evaluate the right Azure OpenAI pattern for your use case. Define data sources, retrieval strategy, context window requirements, safety requirements, and integration points with D365 or custom apps. Deliver solution architecture document.

Use Case AssessmentArchitecture DesignData Inventory

Phase 2 — Week 1–3

Data Preparation & Index Building

Ingest, chunk, embed & index your data

Extract and clean source documents. Implement chunking strategy optimised for your content type. Generate embeddings using OpenAI text-embedding-3-large. Build Azure AI Search hybrid index with semantic ranking configuration.

Data ExtractionChunking StrategyAI Search IndexEmbedding Pipeline

Phase 3 — Week 2–5

Prompt Engineering & Application Build

Design prompts, build API & UI

Design and test system prompts using few-shot examples and chain-of-thought techniques. Build API layer (Azure Functions or App Service). Integrate with front-end (Teams, web app, D365). Implement content filtering and safety layers.

Prompt EngineeringAPI DevelopmentUI IntegrationContent Safety

Phase 4 — Week 4–8

Evaluation, UAT & Production

Measure accuracy, go live, monitor

Run answer accuracy evaluation on test question set. UAT with business users. Production deployment with PTU reservation. Set up LLM observability dashboards for cost, latency, and answer quality monitoring.

Accuracy EvaluationUATPTU DeploymentLLM Monitoring

Industries

Azure OpenAI for Indian Industries

GPT-4o and Azure OpenAI deployed for India-specific use cases — from GST document automation to multilingual customer service assistants.

BFSI · Document AI

Healthcare · Clinical NLP

Manufacturing · Quality AI

Retail · Product Content

Legal · Contract Review

EdTech · Tutoring AI

Real Estate · Proposal AI

Energy · Report Analysis

Azure OpenAI — India Data Residency

SchwettmannTech deploys Azure OpenAI with all supporting infrastructure (Azure AI Search indexes, storage, application layer) in Azure India regions. Your documents, embeddings, and conversation history never leave your Azure tenant. Azure OpenAI model endpoints are available in multiple regions — we architect for compliance with India's DPDP Act 2023 and CERT-In cloud security guidelines, with private endpoints preventing public internet exposure of your AI application.

Business Impact

Proven Results: Azure OpenAI Results

Outcomes from SchwettmannTech's Azure OpenAI engagements across Indian enterprises.

85%

Reduction in manual document review time using GPT-4o automation

4×

Faster RFP response preparation using RAG on company knowledge base

₹50L+

Annual labour savings from document automation per large enterprise client

95%

User satisfaction score on custom Copilot assistants in production

Customer Stories

What Our Clients Say

"SchwettmannTech built a RAG system on our 15-year archive of 400,000 engineering documents. Engineers now ask questions in plain English and get accurate answers with source citations in seconds — instead of spending 2 hours searching SharePoint. Knowledge that was effectively lost is now instantly accessible. The Copilot has become our most-used internal tool within 3 months."

Vikram Rao

CTO · Engineering & Construction, Delhi

"We process 3,000 supplier contracts a year. Azure OpenAI with GPT-4o now extracts payment terms, liability caps, IP ownership, and termination conditions from every contract in under 60 seconds. Our legal team reviews AI-flagged risk clauses instead of reading every page. Contract review time dropped from 4 hours to 20 minutes per contract."

Anjali Sharma

General Counsel · Manufacturing Conglomerate, Mumbai

"Our D365 Sales Copilot — built by SchwettmannTech on Azure OpenAI — coaches sales reps before every customer call: summarising account history, suggesting objection handling, and drafting follow-up emails. Win rate improved 18% in the first quarter. The Copilot is grounded in our CRM data so answers are always specific to our business context, not generic AI responses."

Sanjay Kulkarni

VP Sales · B2B SaaS Company, Bangalore

FAQs

Common Azure OpenAI Questions

Planning a generative AI project? Our Azure OpenAI architects provide free use case assessments to identify the right architecture and realistic outcomes.

Azure OpenAI Service provides the same GPT-4o, GPT-4 Turbo, DALL-E 3, and Whisper models as OpenAI.com but deployed within Microsoft Azure's enterprise infrastructure. Key differences: (1) Data stays in your Azure tenant and is NEVER used for OpenAI model training; (2) Enterprise SLAs with 99.9% uptime guarantees; (3) Integration with Azure security (RBAC, private endpoints, managed identities); (4) Provisioned Throughput Units for consistent latency; (5) Data residency in Azure regions for DPDP Act and CERT-In compliance. For Indian enterprises, Azure OpenAI is the only compliant path to using OpenAI models.

RAG (Retrieval-Augmented Generation) grounds GPT-4o responses in your specific documents by retrieving relevant content at query time and including it in the prompt. Use RAG when your knowledge base changes frequently, when you need source citations, or when you want answers grounded in specific proprietary documents. Fine-tuning modifies the model weights using your data — use it when you need the model to adopt a specific style, format, or handle domain terminology consistently. Most enterprise use cases (Copilot assistants, document Q&A, knowledge bases) use RAG. Fine-tuning is used for specific style adaptation or classification tasks.

We implement multiple layers of hallucination mitigation: (1) RAG grounding — answers must cite retrieved source documents; (2) Answer faithfulness evaluation before deployment using automated test suites; (3) Confidence thresholding — Copilot responds "I don't know" when retrieved context doesn't support an answer; (4) Human review workflow for high-stakes decisions (legal, financial); (5) Ongoing monitoring with user feedback loops to catch and fix accuracy issues in production. No AI system is 100% hallucination-free, which is why we design workflows that keep humans appropriately in the loop for consequential decisions.

Azure OpenAI costs are consumption-based. GPT-4o costs approximately $5 per million input tokens and $15 per million output tokens (prices subject to change). A RAG system handling 1,000 queries/day averaging 2,000 tokens per query (input + output) costs approximately $300–600/month in model costs. Provisioned Throughput Units (PTU) for guaranteed performance cost more upfront but less per query at high volume. SchwettmannTech runs a free cost modelling exercise for your specific use case before implementation — factoring in expected query volume, document size, and retrieval patterns.

Yes — this is one of our core specialisations. Azure OpenAI integrates with D365 in multiple ways: (1) D365 Copilot Studio custom topics calling Azure OpenAI via Power Automate HTTP connector; (2) Dataverse plugin running Azure OpenAI scoring server-side within D365 workflows; (3) Canvas Power App with direct Azure OpenAI API calls for real-time AI features; (4) Power Automate flows using Azure OpenAI to process documents, generate emails, or classify records. We've integrated Azure OpenAI with D365 Sales, Customer Service, Finance, and Business Central.

Build Your First Production GPT-4o Application

Book a free 2-hour Azure OpenAI Architecture Workshop. We'll design your RAG or Copilot architecture, estimate costs, and demonstrate a prototype on your data — no commitment required.

Azure Machine Learning Azure AI Studio

Deploy GPT-4o onYour Enterprise Data