AI that works for Sales
Sellers spend a minority of the week selling. Most of it goes on research, writing, and keeping the CRM tidy enough for the forecast to mean anything.
Are these Sales challenges familiar?
Preparation gets skipped
Proper research before a call takes half an hour nobody has, so the first meeting is spent learning what could have been read in advance.
Proposals are copy-paste archaeology
Each proposal starts by finding a vaguely similar one and editing it, which is slow and quietly ships last quarter's pricing to this quarter's client.
The CRM is a fiction
Notes go in late or never. The forecast is built on fields nobody trusts, so decisions get made on the loudest opinion in the room instead.
What we would look at first.
Whichever of those three your team complains about most. Sales adoption is unusually fragile: if the first thing does not obviously save the seller time in week one, nothing after it gets used.
Briefings before the call
A short, sourced summary of the account, the people and the likely objections, assembled from public information and your own history with them.
Custom Tools & AgentsProposals from your own library
Drafts generated from current pricing and approved language, so the seller edits toward the client rather than rebuilding from an old file.
Custom Tools & AgentsNotes that write themselves back
Call notes turned into structured CRM updates automatically, because the fastest way to fix data quality is to stop asking people to type it twice.
Process Automation