AI Infrastructure & DevOps

A model that works in a notebook and a model that survives production traffic and regulatory audits are different engineering problems. Without autoscaling, observability, and tamper-evident logging, an AI feature is one incident away from an outage.

We build the reliability and evidence layer beneath your AI system: deployment and autoscaling, cost and latency observability on every model call, cryptographic action sealing, and an incident runbook so a rollback is a decision, not a scramble.

• —Standing up deployment and autoscaling for an AI feature going into production for the first time
• —Adding cryptographic audit logs (via PegBit Witness) so compliance teams can verify what your AI did
• —Adding cost and latency observability so model spend is a dashboard, not a monthly surprise
• —Building the incident runbook and rollback plan before, not after, a bad deploy

Often paired with an AI System Architecture engagement — the architecture is what you build, this is what keeps it up and auditable.