VocaiQ is a managed AI voice agent for inbound calls and field service operations. It answers customers, books appointments, qualifies leads, and updates CRM systems. Its AI outbound calling workflows check in with field teams, capture project updates, delivery confirmations, supply requests, and blockers, then turn each conversation into structured operational data inside the systems managers already use. Your team talks. Your systems update.
No reviews yetBe the first to leave a review for VocaiQ
Maker
📌
Hey Product Hunt! I'm Martin, founder of VocaiQ.
We originally built VocaiQ to help small and medium businesses handle inbound customer calls. It answers questions, books appointments, qualifies leads, and keeps CRM workflows updated.
But we found another operational problem worth solving.
Managers of field teams still spend too much time calling workers, chasing project updates, confirming deliveries, collecting supply requests, and manually transferring information into business systems. The workers often do not want another app or another form. They already know how to answer a phone call and speak naturally.
That is the new direction we are exploring with VocaiQ.
A scheduled outbound voice agent can call a field worker, ask structured follow-up questions, capture project status, identify blockers, confirm deliveries, collect material requests, and read the complete update back for verification.
In our latest demonstration, VocaiQ calls an installer to confirm a cabinet project and the next day's delivery. During the same conversation, it captures a request for silicone, hinge caps, and the correct glass shelf supports. The information is verified through a read-back and converted into structured operational data that can be routed to the responsible manager and warehouse workflows.
This is AI outbound calling applied to field service operations.
VocaiQ is not a replacement for managers, field service software, or fleet management systems. It adds a voice capture and follow-up layer that works alongside the systems a business already uses.
The result is a simple operating model:
Your team talks.
Your systems update.
Managers get clearer visibility.
At the same time, VocaiQ continues to handle inbound customer calls, bookings, lead qualification, and CRM updates. The outbound field-operations layer is an additional use case, not a replacement for the original service.
Explore VocaiQ:
https://vocaiq.ai
See the field-operations use case:
https://vocaiq.ai/solutions/fiel...
I would love to hear which operational workflow you would want a voice agent to handle first.
Report
Tested it on a couple of mock inbound calls and the booking flow felt surprisingly natural, the agent actually waited for me to finish rambling before responding. The CRM handoff was the part that impressed me most, clean structured data without me touching a thing.
Report
the part where calls auto-translate into structured CRM updates without anyone retyping anything is honestly the kind of plumbing work most teams skip, and you can tell it was built by people who actually dealt with messy field ops
Report
Would love to see a feature that flags recurring customer pain points across calls, like surfacing the top three complaints each week so managers can spot trends without digging through transcripts. That kind of pattern detection would make the structured data even more actionable for service ops.
Tested it on a couple of mock inbound calls and the booking flow felt surprisingly natural, the agent actually waited for me to finish rambling before responding. The CRM handoff was the part that impressed me most, clean structured data without me touching a thing.
the part where calls auto-translate into structured CRM updates without anyone retyping anything is honestly the kind of plumbing work most teams skip, and you can tell it was built by people who actually dealt with messy field ops
Would love to see a feature that flags recurring customer pain points across calls, like surfacing the top three complaints each week so managers can spot trends without digging through transcripts. That kind of pattern detection would make the structured data even more actionable for service ops.