Praiz automatically captures, structures, and analyzes sales conversations to improve execution, accelerate deal velocity, and drive stronger sales performance.
Praiz helped us build agents aligned with our sales needs. We now have clear visibility on objections, automated coaching, and reliable HubSpot updates.
Nobody really knows where a deal stands beyond what the rep says about it. Records get filled inconsistently, call notes look different from one rep to the next, and the methodology gets applied when someone remembers to.
The result is a forecast built on intuition, rough deal prioritization, and teams repeating the same mistakes.
Most teams buy an AI tool and end up alone in front of an empty setup screen. At Praiz, we configure the agents ourselves, based on your objectives, your documentation and your calls. You can configure it all yourself if you prefer, but that is not the default.
Summarizes everything explicitly stated by the prospect regarding Budget, Authority, Need, and Timing during a sales conversation.
Summarizes everything explicitly stated by the prospect regarding Metrics, Economic Buyer, Decision Criteria, Decision Process, Identified Pain, Champion and Competition during a sales conversation
Captures and structures everything prospects or customers explicitly say about competitors.
Generates a clear, professional follow-up email to send to a prospect after a first meeting.
Evaluates how effectively the salesperson executed a cold call.
Identifies and structures all objections explicitly expressed by prospects or customers during sales conversations.
Yes, and that is the default. We build the agents from your playbook, your documentation and your actual calls. These are not generic templates we leave you to adapt on your own.
Yes. MEDDIC, BANT, SPICED or your in-house criteria: you define the fields to extract and the allowed values, and the agent applies that framework to every conversation.
Any standard or custom field on Deals, Contacts, Companies and Activities. Mapping is configured field by field.
A notetaker produces a free-text summary: the call gets processed and the data stops there. Praiz extracts structured fields (predefined value lists, booleans, numbers) that aggregate from one call to the next. That is what lets you count objections across 200 conversations, map to your CRM properties and query the database. A notetaker produces text, Praiz produces data.
Expect around a month to get set up, then two to four weeks of ramp-up. Praiz configures the agents from your objectives, you review the first outputs, we iterate until the data is clean.
There is nothing for them to do. The bot joins the call, agents run afterwards, fields go to the CRM. No extra data entry is asked of reps.
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