Funnel Stats

Pretty data, visibility, and decision-making. Agents can query this; humans see the state of the machine.

Days lost to missing feedback

Cumulative days candidates waited on feedback this month.

Candidates dying in pipeline

Active candidates with no touch in 5+ days.

Roles burning runway

Open roles cold or at-risk for 2+ weeks.

Offers at risk

Outstanding offers with no candidate response in 3+ days.

Founder attention required

Decisions waiting on the founder.

29d

Avg. time to hire

Applied to accepted, trailing 90 days.

Hiring funnel

Applied

14238%

Screen

5446%

HM Review

2564%

Interview

1656%

Final

967%

Offer

667%

Hired

4–

Darker bars hold more candidates. Right column is conversion to the next stage.

Time in stage

Applied

3.2d

Screen

4.6d

HM Review

5.1d

Interview

6.8d

Final

Offer

5.5d

Darker bars mean candidates spend longer in that stage.

Source quality

Source	Candidates	Hires	Avg. fit score
Referral	34	2	84
Outbound	41	1	78
Inbound	48	0	69
Agency	12	1	81
Sourced	7	0	66

Agents can operate this in plain English

Founder

“What roles are currently burning the most time?”

Operator

“Generate a weekly hiring update for the leadership meeting.”

Recruiter

“Which stage is causing the most candidate drop-off?”