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EPC Group delivers enterprise Azure AI consulting — Azure OpenAI Service (GPT-4), Machine Learning, Cognitive Services, and AI governance. We implement a 7-pillar AI governance framework and configure Azure AI for HIPAA, SOC 2, and FedRAMP compliance. Microsoft consulting experience since 1997. core Microsoft Solutions Partner designations.

Key Facts

  • Azure OpenAI Service provides access to GPT-4, GPT-4 Turbo, Codex, and DALL-E models — all on Azure's compliance-certified infrastructure.
  • Azure AI services can be configured for HIPAA compliance with a Business Associate Agreement (BAA), private endpoints, encrypted data, and audit logs.
  • EPC Group implements a 7-pillar AI governance framework: Model Risk Management, Responsible AI, Data Governance, Security & Privacy, Bias Detection, Explainable AI, and Continuous Monitoring.
  • Azure Confidential Computing (DCadsv5/ECasv5 series) protects data IN USE — not just at rest and in transit — using AMD SEV-SNP and Intel TDX enclaves.
  • EPC Group has Microsoft consulting experience since 1997 and core Microsoft Solutions Partner designations.
HomeServicesAzure AI Consulting
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Enterprise Azure AI Solutions

Last updated by Errin O'Connor, Founder & Chief AI Architect, EPC Group

Transform your business with Azure AI. We offer a range of solutions, including:

  • Azure OpenAI Service (GPT-4)
  • Custom Machine Learning models
  • Cognitive Services
  • AI governance

With experience in the Microsoft ecosystem since 1997, we deliver enterprise-grade AI solutions.

Azure AI Services

Comprehensive Azure AI Solutions

From OpenAI to Machine Learning—we cover the full Azure AI ecosystem.

Azure OpenAI Service

Enterprise GPT-4, GPT-3.5, and DALL-E deployments with private endpoints and compliance controls.

Azure OpenAI Service setup
GPT-4 fine-tuning
Private endpoint configuration
Token optimization
Cost management & monitoring
Custom copilot development
Azure AI Search — vector search, semantic ranking, and RAG architectures

Azure Machine Learning

Custom ML model training, deployment, and MLOps with Azure Machine Learning studio.

ML model development
Azure ML pipeline automation
Model deployment & versioning
MLOps best practices
Automated retraining
Real-time inference endpoints

Cognitive Services

Pre-built AI APIs for vision, speech, language, and decision-making capabilities.

Computer Vision API
Speech-to-text & text-to-speech
Language Understanding (LUIS)
Form Recognizer
Content Moderator
Custom Vision models

AI Governance & Compliance

Enterprise AI governance frameworks ensuring responsible AI, security, and regulatory compliance.

AI governance policies
Model risk management
Bias detection & mitigation
Explainable AI (XAI)
HIPAA/SOC 2/FedRAMP compliance
Audit trail implementation

AI Workflow Automation

Integrate AI into business processes with Azure Logic Apps, Power Automate, and custom solutions.

Document intelligence workflows
Intelligent document processing
Automated data extraction
AI-powered chatbots
Predictive analytics
Process mining with AI
AI Builder (Power Platform) no-code AI for Power Apps and Power Automate
Copilot Studio agents grounded in SharePoint, Dataverse, and Azure data

AI Monitoring & Observability

Real-time AI model monitoring, performance tracking, and automated alerting.

Model performance monitoring
Data drift detection
Prediction logging
Cost tracking dashboards
Alert configuration
A/B testing infrastructure
Our Methodology

Proven Azure AI Implementation Approach

01

Assess

Evaluate AI readiness, identify use cases, data quality assessment, and compliance requirements analysis.

02

Design

AI architecture design, model selection, governance framework, and security baseline establishment.

03

Deploy

Model training, testing, deployment to production endpoints, and integration with existing systems.

04

Monitor

Continuous monitoring, performance optimization, bias detection, and cost management.

Industry Expertise

Compliance-First Azure AI Solutions

Industry-specific AI architectures with built-in compliance.

Healthcare

HIPAA-compliant AI for diagnostics, patient risk prediction, and clinical decision support with full compliance.

HIPAAHITRUSTPHI Protection

Financial Services

Fraud detection, risk modeling, and algorithmic trading with SOC 2 compliance. We map AI workloads to SOC 2 Trust Service Criteria (Security, Availability, Confidentiality) and produce evidence packages for annual SOC 2 audits.

SOC 2PCI-DSSSEC/FINRA

Government

FedRAMP AI solutions for federal, state, and local government with secure deployments. Azure Government Cloud holds FedRAMP High authorization, Azure OpenAI Service is available in Azure Government for FedRAMP workloads, and IL4/IL5 workloads are supported with appropriate controls.

FedRAMPIL4/IL5StateRAMP

Manufacturing

Predictive maintenance, quality control, and supply chain optimization with Azure IoT + AI.

ISO 27001SOC 2GDPR
Why EPC Group

Your Azure AI Partner for Enterprise Success

28+
Years Microsoft Expertise

Gold Partner experience with deep Azure AI knowledge

100+
AI Projects

Enterprise-grade AI implementations

100%
Compliance Success

HIPAA, SOC 2, FedRAMP across regulated industries

24/7
Global Support

Follow-the-sun support model

Frequently Asked Questions

Common questions about our Azure AI consulting services

What is Azure OpenAI Service and how is it different from ChatGPT?

Azure OpenAI Service is an enterprise version of OpenAI models (GPT-4, GPT-3.5, DALL-E) hosted in Microsoft Azure. Unlike consumer ChatGPT, it offers private endpoints, no data retention by OpenAI, HIPAA/SOC 2 compliance, SLA guarantees, and integration with Azure security controls. Your data never leaves your Azure tenant.

Is Azure AI HIPAA compliant for healthcare applications?

Yes. Azure AI services can be configured for HIPAA compliance with Business Associate Agreements (BAA), encrypted data at rest/in transit, private endpoints, audit logs with 6-year retention, and PHI protection controls. We implement Azure AI with HIPAA-compliant architectures including Azure Key Vault, managed identities, and Azure Policy governance.

How much does Azure OpenAI Service cost?

Azure OpenAI pricing is token-based: GPT-4 Turbo is ~$0.01/1K input tokens and ~$0.03/1K output tokens. GPT-3.5 Turbo is ~$0.0005/1K tokens. Exact pricing varies by region and model version. We help optimize costs through prompt engineering, caching strategies, and right-sizing model selection (GPT-3.5 vs GPT-4). Azure AI workloads also have predictable and variable cost components, and we apply FinOps controls to both: Azure Reservations (1-year or 3-year) for predictable GPU and compute VM workloads, Azure Savings Plans to extend compute discounts across instance families, and Azure Hybrid Benefit for BYOL Windows Server and SQL Server licenses.

Can you fine-tune GPT-4 on our proprietary data?

Yes. Azure OpenAI Service supports fine-tuning on GPT-3.5 Turbo and GPT-4 models using your custom training data. We handle data preparation, fine-tuning job execution, model evaluation, and deployment. Fine-tuned models remain private to your Azure subscription and comply with your data residency requirements.

What AI governance framework do you recommend?

We implement a 7-pillar AI governance framework: (1) Model Risk Management, (2) Responsible AI principles (fairness, transparency, accountability), (3) Data governance, (4) Security & privacy controls, (5) Bias detection & mitigation, (6) Explainable AI, and (7) Continuous monitoring. This aligns with NIST AI Risk Management Framework and industry best practices. In practice this means risk classification, model cards, and audit trails for every AI model; content remediation, sensitivity labeling, and Purview integration before AI deployment; private endpoints, CMK encryption, DLP for AI outputs, and role-based access; automated fairness testing on model outputs using Azure Responsible AI tooling; human-readable explanations for AI decisions using Azure InterpretML and the Responsible AI dashboard; and model drift detection, performance dashboards, and incident response alerts.

How long does an Azure AI implementation take?

Timelines vary by complexity: Azure OpenAI proof-of-concept (2-4 weeks), production chatbot (8-12 weeks), custom ML model (12-20 weeks), full AI platform with governance (6-12 months). We use agile sprints to deliver incremental value, with initial POCs often deployed in under 30 days.

What is the difference between Azure AI and Azure OpenAI?

Azure OpenAI Service focuses on OpenAI's large language models, including GPT-4, DALL-E, and Codex. Azure AI encompasses a wider range of services, including Cognitive Services (Vision, Speech, Language), Machine Learning, AI Search, and Responsible AI tooling. Azure OpenAI is part of the larger Azure AI platform.

What is Azure Confidential Computing?

Azure Confidential Computing uses hardware-based trusted execution environments (AMD SEV-SNP or Intel TDX enclaves) to protect data while it is being processed — data in use, not just at rest and in transit. Even the Azure host operator cannot access data within the enclave. It is the right choice for regulated workloads that require cryptographic proof of data isolation: clinical analytics on PHI running on shared Azure infrastructure, financial services M&A modeling with confidential deal data, and federal IL5 workloads requiring hardware-attested isolation. Supported on DCadsv5 and ECasv5 series VMs in Azure.

How much does Azure AI consulting cost?

Each engagement is quoted as a fixed fee after a scoping call. The AI Readiness Assessment, an Azure OpenAI deployment (single use case, governance included, 8-12 weeks) and AI Governance Implementation are each sized to the tenant and the use case rather than sold by the hour. Ongoing managed services include monitoring, retraining triggers, and quarterly compliance reviews.

Ready to Transform Your Business with Azure AI?

Get a free Azure AI consultation. We'll discuss your AI strategy, compliance requirements, and ROI projections.

Schedule AI Consultation(888) 381-9725

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