Sales & Revenuediscovery question memory for sales teams

Give Sales Teams Discovery Question Memory That Makes Every Rep Ask What Works

Sales discovery quality varies wildly per rep. The questions that surface budget, urgency, and decision-making power live in senior reps' habits. AI tools used for discovery prep see one call at a time. MemoryLake gives sales teams discovery question memory based on what's actually worked.

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The problem: sales discovery quality varies by rep without explanation

Top reps surface decision criteria in 20 minutes. New reps don't get there in 60. The difference is the questions asked. The senior reps' framework exists in their habits, not in shared infrastructure.

How MemoryLake captures sales discovery memory

Discovery skill memory

Questions per buying stage and persona.

Reflection memory for effective questions

Patterns from won-deal call analysis.

Per-segment question variants

Different discovery for SMB vs enterprise.

Cross-tool retrieval

Call recording tools, CRM, AI call prep unified.

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How it works for discovery question memory

Connect — Authorize call recording and CRM tools.
Structure — Effective questions become skill memory.
Reuse — Pre-call AI tools retrieve relevant discovery patterns.

Before vs. after: sales discovery memory

	Without MemoryLake	With MemoryLake
Discovery question consistency	Variable	Memory-driven
New rep discovery quality	Months to ramp	Memory access
Cross-rep best practice transfer	Tribal	Captured
Audit discovery completeness	Limited	Memory provenance

Who this is for

Sales enablement and RevOps leaders where discovery quality variance is a known driver of pipeline conversion variance.

Runnable demoabout 5 minutes

Try this use case on your own account

A rep ends the first discovery call with a recap of what isn't there yet: no budget, nobody has agreed to champion it, no other vendor, none of their decision makers has seen a demo, nobody from procurement met. Over five weeks most of that changes. MemoryLake rewrites a "not yet" when a later call says the same thing plainly. When the change comes as a sponsor's offer or a thank-you for joining the demo, the old "not yet" stays, dated the first day, and the sales assistant gives it as today's answer. The app writes each event from its CRM and retires the "not yet" that event ended.

What you will see

The same four calls are stored three times, one project each: the calls only; plus the deal log the app writes (one dated fact per event, fact add + fact update --metadata); plus the ended "not yet"s retired with fact delete, keeping the one that is still true
Over eight runs of the calls-only copy, the budget and the competitor rewrote their "not yet" in place every time; the champion's and the demo's "not yet" stayed every time, and the demo itself was never remembered
Asked through router chat --boundary, the sales assistant answers champion 0 of 23 and demo 0 of 24 from the calls alone ("nobody", "none"); with the app's deal log, 24 of 24 each. Overall 93 of 140, 135 of 140 and 140 of 144
The still-true "nobody from procurement" matters: in the 3 copies where extraction dropped it, every answer was wrong, naming the two people it had met as the procurement team or inventing names. Plus memory and ask subcommands and a local web UI

You need: a MemoryLake API key · the memorylake CLI · Python 3.9+

Run it

git clone https://github.com/memorylake-ai/memorylake-usecases.git
cd memorylake-usecases/none-yet-memory
export MEMORYLAKE_API_KEY=sk-…
python3 demo.py          # or: python3 web/server.py

Open on GitHub Read the walkthrough