The product
AI Gateway sits between every application calling a model and the models themselves. It routes traffic across providers - OpenAI, Anthropic, Bedrock, self-hosted - by cost, latency, and policy. It enforces per-team spend caps. It logs every call with tokens in, tokens out, and the policy applied. When procurement asks where the AI budget went, Gateway tells them. When a provider quietly deprecates a model, Gateway swaps without a code change. It is the control plane you wish you had put in front of the pilot before it grew into four production systems.
Why Manufacturing is different
Manufacturing AI lives at the intersection of ISA/IEC 62443 operational technology security, supply chain traceability (EUDR, DPP, USMCA rules of origin), and ISO 9001 quality management. Agents touching the factory floor route through OT/IT boundary controls that a consumer-grade API call would never survive. Supplier-quality teams need lineage for every component recommendation back to the source document. The commercial side needs bid intelligence that does not hallucinate a specification the engineering team did not actually clear. When an agent writes a spec tolerance into a purchase order, it had better cite the controlled drawing revision it came from, or the quality incident three months later is going to have the CTO&apos,s name on it.
How Gateway plugs into manufacturing reality
For manufacturing, AI Gateway isolates OT-adjacent inference from IT-layer inference. Models scoring shop-floor telemetry run on private infrastructure, corporate knowledge models call commercial providers. Gateway enforces the boundary at the routing layer. Supplier-quality workflows get a dedicated cost bucket so a chatty agent in procurement does not starve the predictive-maintenance team mid-shift.
From proof-of-concept to production
Most manufacturing AI projects die between the pilot demo and the first regulatory review. The demo proves the model can do the task, the review asks whether the system will do it the same way a year from now, whether the audit trail survives a schema change, and whether the vendor will be around to sign the control attestation.
Gateway answers those questions by design. Policies are versioned in source control, not hidden in prompts. Audit trails are first-class artifacts, not log scraps. Governance is a platform feature, not a tab in a spreadsheet. When your manufacturing compliance team meets the system for the first time, they see what they already recognize: a register entry, a validation doc, and a violations feed they can query.
Next step
The fastest way to know whether Gateway fits your manufacturing stack is a 90-minute architecture review. You bring the architecture and the three hardest questions. We bring the deployment patterns we have seen work. The output is a written findings doc - not slides - that your team can use whether or not you end up working with us.
Next step
Map Gateway against your stack in 90 minutes.