Most conversation intelligence tools stop at a transcript and a summary. Praiz goes further: its agents extract specific fields from every call, so each conversation becomes structured data we can query and act on, not a recap nobody reopens.

The agents are custom-built for our use case, and the Praiz team configures them with us instead of handing over a blank builder. That's what made the difference between a nice idea and something we actually use every week.

The macro analysis is where it compounds. Rather than reviewing calls one by one, we see patterns across the entire base: recurring objections, which competitors come up and in what context, product feedback themes. That's visibility we simply didn't have before.

The MCP server is the part I didn't expect to use daily. I can query our whole call base directly from Claude, ask a question in plain language, and get an answer grounded in real conversations without opening the product.

Everything then syncs back into the CRM automatically, so reps aren't doing manual data entry after every call. Review collected by and hosted on G2.com.

Getting full value requires deciding upfront which fields actually matter to you. It's a useful exercise, but it takes some thinking before the payoff shows up. The macro analysis also needs a certain volume of calls before the patterns are reliable, so it's less impressive in week one than it becomes at month three. Review collected by and hosted on G2.com.