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 Banking is different
Banking runs on model risk management - SR 11-7 in the US, SS3/18 in the UK, EU-AI-Act Article 9 for high-risk systems. Every model in production gets a documented validation, an ongoing monitoring plan, a challenger model, and an inventory entry in a central register. Agents that take action on behalf of a customer or a trader are held to the same bar as a decision-support model in underwriting: explainable, auditable, overridable. The model risk management team does not want slides. They want a register entry, a validation doc, and a violations feed they can query. Regulators do not send warnings, they send MRAs and MRIAs. The cost of getting this wrong is not embarrassment, it is a cease-and-desist.
How Gateway plugs into banking reality
In banking, AI Gateway becomes the model-risk-register enforcement point. Every call tagged with the model version, the calling application, the user context, the cost bucket. Spend caps per trading desk, per underwriting team, per operations pod. When model risk management asks for an inventory, Gateway exports it. When a provider deprecates a model mid-quarter, the gateway routes traffic to the challenger model without a code deployment - and the trail shows exactly when the switch happened for the next validation cycle.
From proof-of-concept to production
Most banking 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 banking 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 banking 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.