AI Governance for Manufacturing.
Design engineers, process specialists, supply chain, and quality staff are sending CAD parameters, process recipes, bills of material, supplier terms, and technical specifications into ChatGPT, Copilot, Azure OpenAI, and internal AI tools. The gateway between those users and the model is where trade-secret protection, export-control obligations, and customer confidentiality need to be applied, because the content control plane the LLM provider offers stops at the model boundary and is blind to the customer policy.
DeepInspect runs inline in front of the AI provider. Proprietary designs, process IP, export-controlled technical data, and customer-confidential material are detected and transformed before the payload leaves the customer environment. Every decision is written to a tamper-evident forensic record with the policy version, the actor identity, and the original and transformed payloads preserved. The same configuration applies to interactive chat, retrieval-augmented applications, and autonomous agent workflows that reach manufacturing execution, product lifecycle, and ERP systems.
The risk surface in manufacturing AI
Process IP and proprietary designs inside prompts
Engineers paste CAD parameters, tolerances, bills of material, process recipes, and formulations into AI tools to draft, review, and troubleshoot. This material is trade-secret IP that carries no protection once it leaves the customer boundary except the LLM provider retention agreement, and that agreement covers retention, not the act of disclosure.
Export-controlled technical data
ITAR and the EAR restrict the release of controlled technical data, and a release to a model hosted in or reachable from a foreign jurisdiction can constitute an unauthorized export. The same release to a foreign-person colleague is a deemed export. Staff pasting a controlled drawing or specification into a general AI tool can trigger either one without any intent.
Customer and supplier confidential material
Contract manufacturers and suppliers hold customer designs, program details, and pricing under NDA. Supplier contracts, quotes, and capacity data are confidential commercial terms. An AI summary of a customer drawing or a supplier quote moves that material outside the agreement boundary that was meant to govern it.
Agents reaching plant-floor and engineering systems
Autonomous agents now query manufacturing execution systems, historians, product lifecycle management, and ERP through their APIs. A misrouted tool call or a prompt-injected agent can read production schedules, change engineering records, or expose order data. The control needs to live at the agent gateway, because the downstream system trusts the agent identity.
How DeepInspect applies controls
Technical data and design identifier detection
Deterministic detectors match part and drawing numbers, ECCN and USML references, project codenames, supplier identifiers, and the data classes the company information classification scheme marks as restricted. Each match is redacted, tokenized, or blocked according to the configured action for the user role in effect. Tokenization keeps a reversible mapping inside the customer environment while the upstream model sees only opaque tokens.
Identity-aware and export-status-aware policy
Role identity is supplied by the customer IdP at request time, and the per-role action map can read the export-control status the IdP carries for each user. A US-person engineer and a foreign-person contractor can receive different transformations on the same controlled payload, which keeps deemed-export rules enforceable inside AI workflows. The action map is part of the policy version, so changes are captured in the audit trail.
Evidence-grade forensic record
Every interaction writes a signed record containing the actor identity, the policy version, the rule evaluation path, the original payload, the transformed payload, and the upstream response. The signature anchors integrity. The record is the evidence an export-compliance audit or a trade-secret dispute asks for, and it is queryable against a read-only projection.
Prompt injection and adversarial input handling
Adversarial inputs attempting to override instructions, extract designs, or pivot an agent into restricted systems are scored against the configured detectors and blocked or routed to escalation according to policy. The score, the input, and the action are preserved in the forensic record.
Tool and agent allowlists
Autonomous agents reach manufacturing execution systems, historians, product lifecycle management, and ERP. The gateway enforces allowlists and blocklists on the tools an agent invokes and the data sources it reads. An agent that attempts to call a system outside its allowlist is stopped at the gateway with a record of the attempt and an alert routed to the SOC.
Forensic deep analysis
Patterns across the forensic store surface anomalous access, repeated near-miss policy hits, and the slow exfiltration of design data that single-event monitoring misses. The analysis runs against the customer projection and produces queryable findings that map back to the source interactions.
Regulatory and obligation mapping
ITAR and EAR export controls
The gateway blocks controlled technical data classes from leaving the boundary and applies export-status-aware transformations to foreign-person access. The signed record is the contemporaneous evidence an export-compliance program and a Directorate of Defense Trade Controls or Bureau of Industry and Security review depend on.
CMMC 2.0 and NIST SP 800-171
Defense industrial base contractors handle Controlled Unclassified Information. The access-control and audit-and-accountability control families of NIST SP 800-171, which a CMMC 2.0 assessment verifies, map directly to identity-aware enforcement and the gateway record.
Trade-secret protection
The Defend Trade Secrets Act and state trade-secret law condition protection on the holder taking reasonable measures to keep the information secret. An enforced gateway control over what reaches an external model is one such measure, and the forensic record evidences that it was in place.
ISO/IEC 27001
The Annex A access-control and logging controls expect identity-based access and contemporaneous audit records on every system that handles classified information assets. The gateway record is that artifact for the AI data path.
IEC 62443
Where AI agents reach systems adjacent to the industrial control environment, the gateway enforces the allowlist that keeps those agents inside the segmentation IEC 62443 expects, with a record of every call attempt.
EU AI Act
AI used as a safety component of machinery and other products covered by EU product-safety legislation falls inside the high-risk category. Policy versioning produces the change-control trail relevant to Article 17, the forensic record covers Article 12 record-keeping, and inline enforcement with fail-closed default behavior addresses Article 9 risk management.
The scale of the gap
of organizations across surveyed sectors reported confirmed or suspected AI agent security incidents in the past year. Manufacturing carries the added exposure of export-controlled and trade-secret data inside the same prompts.
of builders cite the absence of auditability and logging as a top concern. Only 7.7% audit agent activity daily, which leaves most manufacturers without the contemporaneous record that an export-compliance audit or a CMMC 2.0 assessment expects.
of teams treat AI agents as identity-bearing entities. The remainder authenticate agents with shared API keys or hardcoded credentials, which makes per-agent attribution and revocation impossible.
Deployment
The gateway runs self-hosted in the customer VPC or on-premises. SaaS and hybrid deployments are available for organizations with different sovereignty requirements. Controlled technical data, design IP, the forensic store, and the transaction object store stay inside the customer boundary in every configuration. For ITAR-controlled programs and other environments that prohibit any public AI service, the full system runs air-gapped against a local inference runtime, with nothing leaving the isolated network.
DeepInspect sits inline between users, agents, and the AI provider. It works with OpenAI, Azure OpenAI, Anthropic, Bedrock, and internal models without requiring a model migration. Existing IdP, SIEM, DLP, and PLM integrations stay in place. Production cutover typically lands inside two weeks for a defined application scope.
Policy on every AI interaction, enforced before data leaves the boundary.