Quality System AI Documentation

This engagement is for quality and manufacturing-engineering teams in regulated industries (ISO 9001, IATF 16949, and similar) who need to author, release, and distribute controlled Work Instructions and SOPs faster and with a stronger audit trail. Today a single Work Instruction takes 2–5 engineer-days to author from a recorded process, redlines are produced by hand and differ between authors, and the shop floor often reads a superseded revision — the leading source of preventable nonconformities.

Quadrant deploys and configures QSAID entirely inside the customer’s own Microsoft Azure subscription. It is not a hosted, multi-tenant product that sits outside the customer’s environment — the application, data, and audit trail all run in the customer’s tenant, under their Microsoft Entra ID, their keys, and their network controls. The engagement is a complete implementation that gets teams new to Azure onto a production-ready, governed workload, and helps teams already on Azure extend their footprint into a new AI and document-control use case, using Azure App Service, Azure AI Foundry, Azure Cosmos DB, Azure Key Vault, Microsoft Entra ID, and Azure Monitor / Log Analytics. Our engineers provide the Azure architecture, deployment, security configuration, integration, and enablement customers typically do not have in-house.

Engagement agenda

Phase 1 — Discovery & Azure foundation (Weeks 1–2)

We map the current authoring and ECO workflow, audit existing document-control and PLM routing, and review the customer’s existing Azure subscription and governance baseline. Where the customer already has a suitable Azure landing zone, we validate and use it; where one is not in place, we provision it — resource group, virtual network, subnets, network security groups, private endpoints, Microsoft Entra ID integration, and Azure Key Vault.

Phase 2 — Build & first product family (Weeks 3–8)

We deploy QSAID to Azure App Service, connect Azure AI Foundry for video-to-step extraction, configure Azure Cosmos DB for controlled snapshots and ECO transaction records, and integrate the customer’s PLM system of record. One product family is taken live end to end — capture, extract, confirm, deterministic redline, cryptographic seal, and closed-loop ECO submission.

Phase 3 — Production rollout & enablement

We harden the workload for production, configure role-based access and per-site permissions through Microsoft Entra ID, enable the write-once audit trail in Azure Monitor / Log Analytics, and hand over run-books and administrator training so the customer’s team can operate and extend the solution independently on Azure.

What the customer receives

• A running Azure workload in the customer’s own subscription — Azure App Service, AI Foundry, Cosmos DB, Key Vault, Entra ID, and Monitor / Log Analytics, deployed and configured on a validated or newly provisioned landing zone.
• Infrastructure-as-code and architecture documentation for the deployed environment, so the customer can redeploy and extend it on Azure.
• A product family live end to end — from recorded process video to a sealed, cited, released Work Instruction with closed-loop ECO submission to the PLM system of record.
• A configured governance and audit baseline — RBAC model, write-once audit trail, run-books, and administrator enablement.

Who it’s for

• Quality engineering and document-control teams that need faster, deterministic authoring and release.
• Manufacturing IT and platform teams adopting or expanding Azure for AI and regulated workloads.
• Regulatory and audit stakeholders that require an immutable, queryable release history.

Delivered virtually via private offer. Timelines are indicative; final scope and price depend on the number of product families and sites, PLM system and integration complexity, and the customer’s existing Azure footprint.