Foundry on the factory floor.
Why 2026 is the year industrial AI ships.
- Manual quality inspection bottlenecks at line speed
- Predictive maintenance signals scattered across SCADA, MES, and ERP
- Supply-chain disruptions and multi-tier visibility gaps
- Shop-floor knowledge trapped in tribal experience and PDF SOPs
- Industrial AI vendors that require cloud connectivity OT can't tolerate
- Quality documentation cycles consuming engineer hours that should be on R&D
Six agent patterns for the plant.
Quality inspection agents
Vision + multimodal agents on the line — defect detection, surface inspection, and dimensional verification with operator-in-the-loop adjudication.
Predictive maintenance
Foundry agents over your historian, MES, and CMMS surface failure signals before they trip the line. Work-order draft and parts pre-stage automated.
Supply-chain orchestration
Multi-agent demand-planning, exception handling, and supplier comms across multi-tier networks. Native fit with Microsoft Fabric for the data layer.
Shop-floor copilots
Operator agents that answer SOP questions, walk new hires through procedures, and capture line knowledge from senior operators before they retire.
Foundry Local on the floor
Foundry Local + Azure Local Disconnected — large multimodal models running fully air-gapped on local NVIDIA GPUs at line speed. Zero per-token cost, zero cloud dependency.
Engineering knowledge agents
Agents over engineering docs, PLM, and lessons-learned databases — your senior engineer's instincts, on tap for the next generation.
What plants see in the first 6 months.
- 30–60% reduction in quality-doc cycle time
- 15–25% reduction in unplanned downtime via predictive signals
- Sub-second inspection latency with Foundry Local on-device
- Shop-floor SOP retrieval in seconds, not coffee-break trips to the office
- $240K/yr return on a $180K initial implementation (4-month payback)
- OT-safe AI that runs disconnected when the network is the constraint
Foundry Local + Azure Local Disconnected.
Common operations questions.
- Can you run AI on the factory floor without cloud?
- Yes — Foundry Local + Azure Local Disconnected (GA Feb 2026) runs large multimodal models on local NVIDIA GPU hardware with the same Foundry APIs as the cloud. Same Agent Framework, zero cloud dependency, zero per-token cost. Critical for OT environments where network reliability or air-gap is non-negotiable.
- Why Microsoft over AWS or Google for industrial AI?
- Microsoft is alone at this scale on OT-edge: Foundry Local on Azure Local lets you run inference at the line. AWS and Google have nothing comparable. Add the existing M365/Dynamics footprint most manufacturers already have, and the case writes itself. Microsoft's Hannover Messe 2026 push (Schneider Electric, Stellantis, Aras, Resilinc on Foundry) is the proof point.
- What about our existing MES/SCADA/ERP?
- We integrate via MCP and standard APIs — Rockwell, Siemens, GE Proficy, AVEVA, SAP, Dynamics, JD Edwards. We don't replace your stack; we make it agent-friendly. Microsoft Fabric handles the data unification layer where useful.
- What's a realistic pilot scope?
- One line, one workflow, one high-value problem — typically inspection or predictive maintenance. We baseline current performance, ship a 4-week pilot, and measure delta. Most clients then scale across lines and plants from a working pattern, not a slide deck.
- Do you handle CMMC for our DoD work?
- Yes — see our /sovereign page for FedRAMP / CMMC / GCC High capabilities. Many of our manufacturing clients run dual postures: commercial cloud for the bulk of operations and Microsoft Sovereign Cloud for CUI/ITAR work.
Pick a fixed-scope sprint.
Foundry Agent Pilot
Production-ready inspection, maintenance, or shop-floor agent for one line.
Multi-Agent POC
End-to-end supply-chain or quality workflow with coordinated specialist agents.
AI Production Kit
Plant-wide rollout with LLMOps, FinOps, and Foundry Local edge deployment.
Have a line that needs agents?
A discovery brief is enough to scope a 4-week pilot — and tell you whether cloud, edge, or hybrid is the right deployment shape.