recruiting · manufacturing · workflow

General Motors saves $2M annually and reduces time-to-schedule by 99.6% with Ev-e conversational recruiting assistant

GM was receiving 1–2 million candidates per year and needed over 55 contracted recruiting coordinators to keep up with screening and scheduling, yet interviews still took 5–7 days to schedule.

How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Candidate contacts via text or chat
Candidates reach GM's recruiting pipeline via text or chat.
Tools used
Ev-e
Outcome

With Ev-e, GM saved $2M annually through hiring automation and achieved a 99.6% decrease in time-to-schedule, reaching candidates in the way most convenient for them with no time investment from recruiters.

Results
Time saved99.6%
Volume1–2 million candidates per year
Cost replaced$2M
Source

https://www.paradox.ai/case-studies/general-motors

How we source this →

Grounding & classification
Source type: vendor customer story
25 fields verified against source quotes.
ai agentconversational aichat transcriptmetric backednamed customerproduction runtime claimedtools describedworkflow describedautomotivemanufacturingcost reductioncycle time reductionemployee productivitytime savedvendor customer storyappointment schedulinghr opsrecruitingautonomous resolutionintake to triage