OpenNashPrepared for Dan HirleaDan Hirlea / Head of Artificial Intelligence / Homeprotect
We did the homework
on Homeprotect.
Homeprotect already has a serious AI base. We found three queues where OpenNash can add delivery capacity without distracting your AI team from the platform work.
Three places we would start.
Pick one workflow. We automate the prep work for 14 days and show whether it can delay a hire, reduce rework, or move people to higher-value queues.
Claims handlers need complete evidence packs.
Public roles describe rapid claims, policy checks, damage assessment, supplier coordination, settlements, and customer records.
We collect FNOL details, policy context, estimates, messages, and settlement rationale before a handler reviews.
AI assurance needs samples, not slideware.
Risk and compliance work names FCA, Consumer Duty, testing, dashboards, control gaps, remediation, and AI implications.
We sample claims, complaints, AI outputs, and sales flows, then draft exception notes and remediation trackers.
GCP pipelines should not become another support queue.
The data engineering role points at BigQuery, dbt, Airflow, APIs, SFTP, streaming, observability, alerting, and runbooks.
We monitor source freshness, draft backfill steps, update runbooks, and summarize business impact when data is late.
Dan, give us 30 minutes.
Bring one Homeprotect queue your team would rather stop babysitting. We will make it worth your time with the automation map, hire-pressure math, and a 14-day no-charge start.