What RevenueRep.ai is
RevenueRep.ai turns a sales team's calls into records you can search, measure, and ask questions about.
It listens to the calls a team already makes, writes down what happened on each one, and puts that in front of the people who need it: as a dashboard, and as Rev, an assistant who answers questions about the calls with the calls themselves.
How it works
Three steps, in order.
- 1
Calls come in
RevenueRep.ai connects to where a team's calls already happen: a dialer, Zoom, CallRail, uploaded recordings, or the Chrome extension that records browser calls. A CRM such as Salesforce can be connected too, so calls line up with the deals they belong to.
- 2
Each call becomes a record
Every call is transcribed and written down as structured fields: the outcome, the objections raised, the questions the customer asked, commitments made, and the next step. Each field points back to the line of the transcript it came from, and the original recording and transcript are kept.
- 3
The team reads it
Those records feed a dashboard of calls, analytics, objections, customer journeys, coaching, and pipeline health, and they feed Rev, an assistant who answers questions about the team's calls in the dashboard, Slack, or Telegram and cites the calls he drew on. Rev can also act in connected tools, and proposes each change before it is made.
Who uses it
One workspace, three views of it.
- Reps
- See their own calls, a debrief after each one, and the guidance and follow-ups that came out of it.
- Managers
- See the team's numbers over time, review calls, coach against what actually happened on the phone, and ask Rev why a number moved.
- Owners and admins
- Connect data sources, map fields and outcomes, watch data quality, and decide what Rev is allowed to read and do.
Where the data goes
Each workspace is its own.
A team's calls, transcripts, and records live in a workspace that the database itself keeps separate from every other workspace. Original recordings and transcripts are preserved, and call data is not used to train models. The security page describes how this is enforced, the subprocessor list names every vendor that handles the data, and the privacy policy covers the rest.
Questions? Write to hello@revenuerep.ai.