Manufacturing and industrial environments operate with some of the most sensitive and proprietary data in any industry. From CAD drawings and production metrics to supplier contracts and regulatory filings, this information is often protected by NDAs, ITAR, EAR, ISO 27001, or CMMC requirements.
Your teams depend on a web of interconnected systems—MES, ERP, SCADA, quality audits, SharePoint sites, file shares, and legacy applications. But that data is fragmented, difficult to search, and often trapped in systems that weren’t designed for modern AI.
Public SaaS AI tools weren’t built for this.
They fall short in critical ways:
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They transmit prompts and data to external servers, violating data residency and confidentiality expectations
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They retain your queries by default, introducing risk of long-term exposure or vendor access
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They can’t integrate with on-prem systems like MES, ERP, SCADA, or local file shares without replicating data to the cloud
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They don’t operate well in segmented, zero-trust networks where outbound access is restricted
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They offer no clear audit trail, leaving you blind to how results were generated or what internal data was used
For teams that prioritize security, traceability, and operational control, these limitations are unacceptable.
IronCloud takes a different approach.
Instead of sending your sensitive information to a third-party model, IronCloud runs entirely inside your infrastructure—on a private cloud, secured network segment, or locked-down VPC. It integrates with your existing tools—MES, ERP, SharePoint, Jira, Confluence, and others—and makes them searchable, explainable, and actionable through secure AI interfaces.
You get the speed and intelligence of modern LLMs—without giving up ownership, control, or compliance. Prompts never leave your network. Completions are not logged or reused. And every interaction is traceable and auditable by design.
This is AI built for your environment. Secure, connected, and aligned with the way manufacturing actually works.