Every meeting generates decisions. Most of them evaporate.
Your team leaves a 90-minute L10 with a dozen action items, three strategic calls, and two unresolved debates. By next week, half of that is gone — not because people forgot, but because there was no system to catch it.
This is what we call the meeting-data problem. The highest-signal conversations your company has — where strategy gets decided, where problems get named, where accountability gets assigned — happen in rooms with no structured capture.
Most companies try to solve this with notes. But notes are passive. They sit in a Google Doc someone bookmarked once. They don't surface when you need them. They don't connect decisions to outcomes. They don't answer the question "Wait, why did we decide that?"
At BrainGem, we've been running our operations on Freddy — our AI assistant — since we started. Every L10, every founder directive, every escalation gets captured in a structured way that Freddy can actually use. When someone asks "What did we decide about the partner program?" Freddy doesn't say "Let me check the notes." Freddy knows.
The result: decisions have memory. Context survives personnel changes. New team members can ask questions that used to require a 45-minute onboarding call.
If your meetings are good and your institutional memory is bad, you have a data architecture problem. The good news: it's solvable. The bad news: notes alone won't solve it.
What would change if your company could query its own decision history the way you query a database?
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