DashboardLim Build · Sales intelligence
Every sales and client conversation is captured, structured and centralised into one searchable company memory the whole team can ask questions of. Built for our own sales operation, held to the same evidence and human-control standards we apply to client systems.
Operator case study
841+ calls remembered
4 recording sources
9 workflows
Human approval kept
See how a recorded call becomes searchable company memory the whole team can ask questions of.
841+
recorded calls in one memory
551+
structured summaries written
4,027+
searchable memory records
4
recording sources unified
Instead of searching recordings, notes and CRM history, the team asks the memory directly and gets the whole relationship back in seconds.
“Tell me about [client]: what are we discussing, what solution are we proposing, the deal context, the latest conversation and the next step?”
Every week, your team has the conversations that decide your pipeline. Setter calls, discovery calls, demos, check-ins with existing clients. Most of what is said in them never makes it past the call itself.
Notes depend on whoever took the call remembering to write them. Recordings scatter across tools, so a deal's history thins out one conversation at a time. The CRM ends up knowing whatever somebody happened to type.
The cost arrives later: proposals that miss what the client actually asked for, handoffs that lose the context, and follow-ups that re-ask questions the client already answered.
Four recording habits, no shared knowledge.
Notes by memory Details survived only if someone typed them up after the call.
Scattered recordings Every tool was another place a deal's history could hide.
Thin CRM records Deals moved forward on whatever the CRM happened to know.
Nine workflows, one pipeline, nothing written by hand.
tl;dv, Gemini, GHL and Loom recordings arrive automatically after each conversation.
Each call lands in one central table with its full text. Nothing lives only in a recording tool.
AI types each call (setter, discovery, follow-up, client check-in, onboarding) and routes it down the right path.
A clear summary of what was said, decided and promised, ready for a person to review.
From the end of the conversation to the start of the next one.
The full transcript becomes a structured brief covering the conversation, objections, decisions and agreed next steps.
The brief is formatted so the team can scan the call and verify the important details quickly.
The summary, deal context and proposed action post to the sales channel for review.
Six layers between the conversation and the answer.
Where calls come from
The automation backbone
The system drafts. People decide. Every summary waits for a human approval before anything is written to the CRM. Approval is a safety detail built into the pipeline, not an afterthought.
Calls contain prospect conversations, so they stay inside the company. This page shares architecture and aggregate metrics only, never call content.
The system drafts; people decide
Every CRM write requires approval
Transcripts and summaries remain internal
Public copy uses aggregate metrics only
Counted against the running system, stated as floors that only grow.
Every one stored with its full transcript in one place.
Written by AI across the stored calls, reviewed by people.
Queryable before the next conversation.
tl;dv, Gemini, GHL and Loom feeding one memory.
Every call starts informed The team retrieves the full history before the next conversation instead of re-listening to recordings.
Proposals quote the client Drafts use what was actually said on the calls, not what somebody remembered.
Handoffs carry the whole story Onboarding receives the complete sales history, not a summary of a summary.
Knowledge compounds Each conversation makes the next one sharper; the memory gets more valuable with every call.
The boundaries are part of the design.
CRM approval remains human. No summary reaches the CRM on its own.
Follow-up drafts stay review-first and are never auto-sent.
Call scoring is outside the current scope, by choice.
People decide what to ask the memory. It answers, they judge.
Teams whose best intelligence dies inside recordings.
Founder-led agencies running setter or discovery calls
B2B service teams whose deal history should not depend on memory
Sales teams tired of re-listening to calls before the next one
Operators who want AI speed with human control kept in place
Related resources
Built on your stack. Owned by you. Shipped in weeks.
9
workflows feeding the memory
A real question asked of the live company memory, with the client and commercial details masked. This is what the team gets back before the next call: no searching, no re-listening, no digging through CRM history.
Repeated questions Without the history, the next call started from a blank page.
Every call is embedded into a searchable store, so past conversations can be queried like company knowledge.
A person approves each summary. Only then do the CRM note, the follow-up draft and the next step land.
A person checks the summary, corrects anything inaccurate and approves or holds the CRM write.
The deal gains the call note, confirmed next steps and a follow-up email draft, linked to the right record.
The call joins the searchable memory, so the next conversation starts with everything this one taught us.
Understanding each call
Where knowledge accumulates
The approval that stays
Where approved work lands
Case study
We replaced scattered sales reporting with a single live sales performance dashboard — every deal, stage and automation signal in one screen, refreshed automatically every day.
