Azure-Native

AI Assistant Hub for Websites & Business Channels

Turn your website into a multilingual digital workforce — with AI assistants for Sales, Support, Customer Service, and HR, plus optional email automation.

This is not a generic chatbot. We start from a proven core platform, then customize the UI, content, workflows, and RAG knowledge architecture to match your business.

What it does

Answers customer questions 24/7 in their language

Uses your approved knowledge (PDF, Word, Excel, internal pages, databases)

Routes requests to the right team (Sales / Support / HR)

Captures leads with smart forms and conversation insights

(Optional) Reads inbound emails and drafts replies for approval

(Optional) Voice: speak & listen on the website

Department-specific AI agents

📈

Sales Agent: qualifies leads, suggests next steps, drafts proposals and follow-ups

🛠️

Support Agent: technical help based on your manuals, FAQs, and ticket history

👥

HR Agent: internal policy Q&A, recruiting intake, candidate pre-screening

📧

Email Agent: reads inbound emails, drafts replies, routes to owners, approval workflow

Multi-Agent & Model-Agnostic Architecture

Optional multi-agent orchestration: stay model-agnostic — use the GPT-5 family (e.g., GPT-5.2 / GPT-5.1) and, where licensed, other models (e.g., Claude) behind an orchestration layer / Microsoft Agent Framework, with the option to add more models over time.

GPT-5.2 GPT-5.1 Claude Model-Agnostic Microsoft Agent Framework

"Grounded" answers (reduced hallucinations)

With RAG (Retrieval-Augmented Generation), the assistant answers based on your company's sources — and can return citations to the original documents.

Enterprise security & privacy

Runs on Microsoft Azure (single-tenant per client if required)

Role-based access for admins and content owners

Encryption at rest and in transit

Optional Private Network / Private Endpoints

Auditing, logging, and monitoring (Application Insights)

For Technical Teams (Architecture Overview)

Core building blocks (typical):

  • Azure OpenAI / Azure AI Foundry for LLMs (model-agnostic, latest GPT family supported)
  • Azure AI Search for retrieval + hybrid search
  • Azure Storage for document management (admin upload & categorization)
  • Azure Document Intelligence (optional) for PDF extraction & structuring
  • Orchestration layer / Agent framework (multi-agent routing, tool use, workflows)
  • .NET / Blazor front-end + Web API backend
  • Azure SQL / SQL Server for business data and app state
  • Azure Key Vault for secrets and keys

Key capabilities:

  • Knowledge segmentation by department, product line, region, or customer type
  • Admin console for upload, taxonomy, re-index, and content lifecycle
  • Conversation memory (safe), summarization, lead scoring, escalation rules
  • Email workflow integration (e.g., Microsoft Graph) with approval gates
  • Observability: trace prompts, citations, latency, and cost controls

RAG Architecture for Website Assistant

Our website AI assistant is powered by a production-grade Multi-Agent system built on Microsoft Agent Framework.

Microsoft Agent Framework — Orchestrator
Tool Gateway RBAC / Approval / Audit
📈 Sales
🛠️ Support
👥 HR
📧 Email
AI Search
Azure SQL
Blob Storage
Azure OpenAI

Why Microsoft Agent Framework?

  • Native C#/.NET — first-class integration with Blazor and ASP.NET Core
  • Official Microsoft Multi-Agent framework with stable API
  • Built-in Plugin system for Tools (RAG, SQL, APIs)
  • Multi-Agent orchestration with intelligent routing and hand-off
  • Tool Gateway with RBAC, approval gates, and audit logging

Specialized Agents

  • Sales Agent: service inquiries, pricing, lead capture, demo scheduling — with RAG over company knowledge base
  • Support Agent: technical help, documentation search, customer history from Azure SQL, ticket creation
  • HR Agent: resume analysis, candidate comparison, hiring workflow with human-in-the-loop approval
  • Email Agent: inbound email processing, draft replies, routing to owners, approval workflow

Shared Infrastructure

🔍 Azure AI Search — vector + hybrid search for RAG retrieval
🗄️ Azure SQL Database — business data, customer history, conversation state
📂 Azure Blob Storage — document management with admin upload and categorization
🤖 Azure OpenAI — GPT family models for LLM inference
🛡️ Tool Gateway — RBAC enforcement, allowed-tools policy, human approval gates, audit logging

Delivery Approach

1

Discovery

goals, data sources, languages, security constraints

2

MVP

core assistants + RAG + admin upload + reporting

3

Production

hardening, governance, monitoring, scaling, rollout

Ready to transform your website?

Let's discuss how AI Assistant Hub can work for your business.

Get in Touch