All demos
    Demo 09 · Azure AI Agent Blueprint

    The Complete Azure AI Agent Blueprint: From Gateway to Production

    This is the full picture of a production AI-agent platform on Azure. Press play to watch a request travel layer by layer — from Microsoft 365 / Teams / Copilot through the Application Gateway and API Management into agents hosted in Container Apps, out to knowledge and memory in the Context Layer, and into Azure AI Foundry for reasoning and custom-model fine-tuning. Hover any service to trace its connections.

    Azure
    AI Agents
    Azure AI Foundry
    RAG · Memory
    Share
    Loading the interactive walkthrough…

    Explore another walkthrough

    Demo 01

    dbt + Medallion Architecture

    Watch a messy orders.csv get progressively refined by dbt models — with lineage, tests, macros and incremental builds.

    Demo 02

    SQLMesh vs dbt

    A standalone look at where SQLMesh diverges from dbt — stateful incrementals, built-in audits, column-level lineage and virtual environments — and the situations where it's the better choice.

    Demo 03

    Master Data Management

    Watch the same customer — scattered across CRM, ERP, e-commerce and support with conflicting data — get standardized, matched, merged into a Golden Record, and synced back to every system.

    Demo 04

    Change Data Capture (CDC)

    Watch inserts, updates and deletes from an operational orders table get captured and streamed into Bronze → Silver → Gold — with a side-by-side of log-based, query-based and trigger-based capture.

    Demo 05

    Banking

    Submit a sample loan form and watch a workflow fire node by node — webhook, credit check, risk scoring, decision branch, core-banking update and notifications — replacing days of manual hand-offs.

    Demo 06

    AI Support

    Submit a real support message and watch a live workflow use AI to classify it, set priority, route it to the right team and draft a reply — actually running on the backend, not a simulation.

    Demo 07

    Finance / AP

    Step through a workflow that runs a 3-way match of a vendor invoice against the purchase order and goods receipt — pausing for a receiving check and approval before posting to the ERP.

    Demo 08

    Apache Kafka · Streaming

    A no-fluff explainer of how Kafka moves data, the real-world challenges of running it, and a side-by-side of Kafka vs. Azure Stream Analytics, AWS Kinesis, Google Pub/Sub and managed Kafka.

    Demo 10

    AWS AI Agent Stack

    An interactive, animated AWS reference architecture: watch a request flow through ALB and API Gateway into ECS Fargate agents, out to Bedrock Knowledge Bases and Kendra for RAG, DynamoDB/ElastiCache memory, and SageMaker + Bedrock for reasoning and fine-tuning.

    Demo 11

    Google Cloud AI Agent Playbook

    An interactive, animated Google Cloud reference architecture: watch a request flow through Cloud Load Balancing and Apigee into Cloud Run / GKE agents, out to Vertex Vector Search and the RAG Engine, Firestore/Memorystore memory, and Vertex AI + Gemini for reasoning and tuning.

    Demo 12

    Data Platform Architecture

    An interactive, animated data-platform architecture: watch data flow from operational sources through CDC, streaming and batch ingestion into a Bronze → Silver → Gold lakehouse on an open table format, then out to BI, SQL, ML and real-time serving.

    Demo 13

    Enterprise RAG · Security & Governance

    Take RAG inside the company: sync SharePoint, Confluence and shared drives, filter retrieval by each user's permissions, redact sensitive data, and measure answer quality before rollout.

    Demo 14

    Data Quality & Observability

    Catch bad data before it reaches your dashboards — automated quality checks, anomaly detection, lineage and alerting across the pipeline.

    Demo 15

    RAG · Retrieval-Augmented Generation

    Watch a question flow through a Retrieval-Augmented Generation pipeline — documents chunked and embedded into a vector database offline, then a query embedded, top-k chunks retrieved, and the LLM answering grounded in real, cited text.

    Demo 16

    3NF vs. Data Vault

    The old Inmon-vs-Kimball argument is back, and this time it's about the silver layer of the medallion architecture. Should silver be modeled in Inmon-style 3NF, or as a Data Vault 2.0 raw vault?