AI AUTOMATION SEATTLE

Seattle buyers think in systems, so we build like it: automation as maintained infrastructure, not a one-off script. Versioned, monitored, with runbooks and owners. Support AI evaluated against real ticket sets; ops workflows with idempotency and retry logic; data pipelines with freshness SLAs and anomaly alerting.

The patterns: e-commerce customer service AI grounded in order, inventory and policy data; seller and vendor onboarding workflows; internal IT/HR assistants deflecting the repetitive ticket load; reporting pipelines that give every team the same numbers. All of it instrumented — if you can't measure it, we don't ship it.

We don't sell 'AI transformation'. We sell one workflow at a time: mapped, measured, automated, and monitored. The audit comes first — two to three weeks watching how the work actually flows — then a pilot with numbers attached. It is slower than a slide deck and considerably more useful.

No Seattle office, no sales layer — you talk to the engineers building your automation. We're in Manchester, working across the Atlantic with a daily overlap window for reviews and unblock calls. Our clients keep us because the work is measured: hours returned, error rates down, cycle times shortened.

Platform thinking cuts both ways: automation must be as reliable as the infrastructure it joins. Our Seattle builds include monitoring, alerting, rollback procedures and human approval on consequential actions — because an automation outage at scale is worse than no automation.

Second, on where the human sits: inside the loop, not watching it. Drafts get reviewed, flags get triaged, exceptions get a person. Fully autonomous customer-facing agents are a liability dressed as efficiency — we build supervised automation and say so upfront.

For the wider picture, CISA's AI guidance is worth a read before connecting AI to anything critical — national direction shapes what is sensible to build today versus next year.