Praiz turns conversations into reliable CRM data to enforce processes, measure execution, and speed up decision-making.
Praiz was the only solution able to integrate with our custom workflows to extract highly qualitative data thanks to their AI features.
Your reps fill in the CRM from memory. Without reliable data from your conversations, everything you build on top of it, forecast, dashboards and AI agents, runs on what someone chose to type in.
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.
Automatically evaluates whether a deal is qualified or not based on customizable qualification criteria and what was actually said during the sales call.
Summarizes everything explicitly stated by the prospect regarding Metrics, Economic Buyer, Decision Criteria, Decision Process, Identified Pain, Champion and Competition during a sales conversation
Identifies and structures all objections explicitly expressed by prospects or customers during sales conversations.
Captures and structures everything prospects or customers explicitly say about competitors.
Evaluates how effectively the salesperson executed a cold call.
Evaluates how effectively the salesperson conducted a discovery call.
It pushes free text into a notes field. Praiz extracts typed fields (predefined value lists, boolean, number, text) and maps them to your CRM properties, custom fields included. That is the difference between a note someone rereads and data you can build a report or an automation on.
Deals, Contacts, Companies and Activities. Standard and custom fields are both supported. Custom objects are not.
Yes. Each field has two independent settings: whether to include it in the note pushed to the CRM, and whether to map it to a CRM property. A ten-field agent can push only eight.
Not natively. We use a short text field with a format enforced in the prompt, which then maps to a CRM date field. It is a workaround that works, not a native type.
Through webhooks, which return agent outputs, the raw transcript and metadata once the call is fully processed. The MCP server additionally lets you query the database from Claude, ChatGPT or Gemini.
No. Praiz structures the data inside your conversations, not external B2B data. That is a different job from a contact enrichment tool, and the two complement each other more than they overlap.
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