[AUTODESK + MICROSOFT] YOUR COMPETITIVE EDGE

AI-Enable Your Autodesk
+ Microsoft Stack

We build CAD viewing and extraction workflows on Autodesk APS, then deploy agentic AI securely on Microsoft Foundry—so industrial teams automate quoting, drawing review, quality inspection, and operations without replacing their existing tools.

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LAYER 1

Autodesk APS: Unlock the Design Data

Most design data is locked inside CAD files. APS (Forge) breaks that lock—translating models to SVF/SVF2, extracting metadata and object trees, enabling browser-based viewing, markup, and programmatic access to geometry and properties.

LAYER 2

Microsoft Foundry: Deploy AI at Enterprise Scale

Azure AI Foundry gives the extracted design data a brain—multi-agent orchestration, RAG over your documents, function calling into ERP/CRM, and production deployment with Entra, APIM, Monitor, and containerized services.

Why the APS + Foundry Combination Wins

Most consultancies do either “generic AI” or “generic CAD tooling.” Very few combine CAD data extraction via APS with enterprise-grade agentic AI on Foundry. That combination is rare—and it’s the exact wedge industrial teams need.

10x

Faster quoting when CAD metadata feeds directly into ERP/CPQ via an AI agent.

CAD licenses needed for sales, procurement, or shop floor to view and annotate drawings.

100%

Azure-native—your data never leaves your tenant. Full enterprise security and compliance.

What These Workflows Look Like

Four agentic workflow patterns we deliver for industrial teams.

RFQ → BOM → Estimate

Customer uploads a drawing or PDF → APS extracts parts list and metadata → AI agent generates BOM and pricing estimate → pushes to ERP/CPQ for approval. Quoting time: days → minutes.

APS Model Derivative → GPT-4o → ERP API

Design Review Agent

Compare drawing revisions via APS → AI agent detects geometric and annotation changes → generates a structured change report → routes issues to engineers in your project management tool.

APS Diff → Foundry Agent → Jira/Teams

Vision QA Agent

Real-time camera feed → vision model detects defects → AI agent compares against drawing specs extracted by APS → auto-generates inspection report → continuous learning loop from operator feedback.

APS Specs + Vision AI → Foundry → QMS

Ops Copilot

Maintenance tickets + sensor data → AI agent retrieves relevant drawing sections, equipment manuals, and historical fault data → generates prioritized root cause suggestions and recommended actions grounded in your SOPs.

APS Drawings + RAG → Foundry Copilot

Frequently Asked Questions

Do we need to be an Autodesk customer to use APS?

Not necessarily. APS (Forge) works with files from many CAD tools—not just Autodesk products. The Model Derivative API can translate DWG, DXF, RVT, IPT, STEP, IGES, PDF, and many other formats. You need an APS account (available through Autodesk’s developer program) and your CAD files—but you don’t need Autodesk product licenses to use the APIs.

What existing Azure services do we need for Foundry?

At minimum: an Azure subscription and Azure OpenAI access. The broader Foundry stack builds on existing Azure services you likely already have—Entra ID, Container Apps or AKS, Azure Storage, and Azure Monitor. Kamna starts with what you have and layers in only what’s needed for your specific workflow.

How do you handle data security when processing CAD files?

CAD files are processed in your own APS tenant (your OSS bucket)—Kamna never touches your proprietary design data. AI inference runs on your Azure OpenAI instance within your tenant, with private endpoints preventing exposure to the public internet. We implement data classification via Purview, and all access is audited through Entra ID logs.

What’s a realistic starting point for a small manufacturing team?

The highest-ROI starting point for most SMEs is quoting automation: upload a drawing, extract the BOM, generate an estimate. It’s a self-contained workflow with a measurable outcome (time saved, quote accuracy) and doesn’t require changing your existing ERP or PDM. Kamna delivers this as a 30–45 day pilot with a clear go/no-go evaluation before any broader investment.