AI Automation
After-hours facilities dispatch that pages the right technician, not the whole roster
Helio’s night desk broadcast every alarm to a group chat. We built dispatch automation that reads the alarm, checks who is on call, and pages one technician with the building context.
The operational problem
HVAC, access, and plumbing alarms all landed in the same thread. On-call techs ignored noise until something was actually flooding.
Response time on real emergencies suffered because the channel trained people to wait. Clients measured that wait.
What was breaking down
- Group texts with no building history
- No skill matching for the trade required
- Morning recap assembled from screenshots
How Striders Tech approached it
We treated dispatch as a product: classify the event, attach the site packet, pick one on-call tech by skill and location, and only escalate if they decline.
What we built
- Alarm classification with site and asset context
- On-call calendars with trade skills
- One-tap accept/decline from mobile
- A morning log operations can hand to the client
Results the team can measure
- 63% fewer broadcast pages to techs who could not help
- 22 min median accept-to-en-route on critical HVAC
- Client SLAs met through summer without adding a second night coordinator
Who this case study is for
Facilities firms that sell response time and currently run nights on a group chat.
Helio Facilities operates in facilities management. The work is a custom system designed around their process, not a generic template with extra fields bolted on.
What changed after the system went live
fewer broadcast pages to techs who could not help
median accept-to-en-route on critical HVAC
met through summer without adding a second night coordinator