The model is the easy part.

The engine underneath is the hard part.

Point a model at your calls and you get answers that are wrong, brittle and expensive. Format fixes all three. Every conversation structured and ready for whatever you build on top.

See what’s underneath

01. SourceWhere the conversations come from.02. StructureWhat happens to them.03. BuildWhat you build on it.

Source. Structure. Build.

01. Source

Pull in your customer conversations, from wherever they’re recorded.

Call recorders, support platforms, CRM.

Plugs into Gong, Fathom, Fireflies, Granola, Intercom, HubSpot, Salesforce and 30+ more.

01. Source

Pull in your customer conversations, from wherever they’re recorded.

Call recorders, support platforms, CRM.

Plugs into Gong, Fathom, Fireflies, Granola, Intercom, HubSpot, Salesforce and 30+ more.

02. Structure

Every need, objection, complaint and buying signal becomes an insight.

Each one is tied to the company and the person who said it. We cluster them, count them, and watch how they evolve over time.

02. Structure

Every need, objection, complaint and buying signal becomes an insight.

Each one is tied to the company and the person who said it. We cluster them, count them, and watch how they evolve over time.

All conversations

Every insight, by topic

Grouped into themes

Segmented

Over time

03. Build

Put it to work anywhere.

Ask Claude. Brief an agent. Pull insights into Linear, Notion or Jira. Your AI finally has the evidence it was missing.

Connects to Claude, ChatGPT and any agent you run.

03. Build

Put it to work anywhere.

Ask Claude. Brief an agent. Pull insights into Linear, Notion or Jira. Your AI finally has the evidence it was missing.

Connects to Claude, ChatGPT and any agent you run.

Explore

Browse the themes your customers raise. Open one to see how widespread it is, who it affects, and exactly what they said.

Acme Corp

Flag numbers built on too few records

Show how much data sits behind each number before people rely on it.

When it’s mentioned

Who’s mentioning it

8companies

Customers 5Prospects 3

Evidence

20 insights

“A chart built on four deals looks as solid as one built on four hundred. I need to tell them apart.”

Tom AdlerProduct Ops Lead · Evrin PackagingGong · 3 days ago

Analyze

Bring the same evidence into a report. See the numbers, understand the context, and share what matters with your team.

Acme Corp

Custom reportLast 6 months

Teams want to know how sure each number is.

Teams already see where each number comes from.
Now they want to see how much data backs it.

Data trustSOJLShared with your team

8 companies ask to flag numbers built on too few records. The need is consistent: show how much data sits behind each number before people rely on it.

“A chart built on four deals looks as solid as one built on four hundred. I need to tell them apart.”

Tom AdlerProduct Ops Lead · Evrin PackagingGong · 3 days ago

What to build

A record count on every number.
A warning when the count is low.

Query

Use the AI tools you already work in. Get an answer grounded in the same customer conversations, with the sources to back it up.

ClaudeAcme Corp data trust

What do teams need before they trust a number?

Above all, a way to flag numbers built on too few records. 20 insights from 8 companies point to two things:

Show the data behind each number. Its record count, so nobody mistakes four deals for four hundred.
Warn before people rely on it. Mark a number as thin when only a handful of records back it.