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FlashCat.aiAI BOS

The AI Business Operating System

AI & Intelligence

Decision Ledger

A real Decision Ledger: log a decision's alternatives and your actual stated confidence the moment it's made, then come back and record what really happened -- closing a loop almost no business software ever closes. Precedent search surfaces similar past decisions and how they actually turned out before you make a new one.

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5Features
3Benefits
0Industry Clouds

Problems Solved

  • •Nobody ever goes back and checks whether a past decision or forecast was actually right.
  • •The same debate gets re-litigated because nobody remembers what was tried before, or why it did or didn't work.
  • •"How good is our judgment, really?" has no real answer -- just opinions.

Benefits

  • A real, checkable record of judgment over time instead of just opinions
  • Institutional memory that survives someone leaving -- precedent is queryable, not stuck in one person's head
  • Confidence that's actually calibrated against reality, not just asserted

Features

Structured capture: title, alternatives considered, and a 0-100 confidence estimate at decision timeScheduled review reminders -- a real notification when a decision's review date arrivesOutcome recording: what actually happened, rated Good/Mixed/BadCalibration summary: average stated confidence broken down by how decisions with a recorded outcome actually turned outPrecedent search: real keyword-overlap matching against past decisions with a recorded outcome, surfaced while logging a new one

How It Actually Works

1

Decision logged

Title, description, alternatives seriously considered, and a real 0-100 confidence estimate are captured at the moment the call is made -- not reconstructed afterward.

2

Precedent checked

As it's typed, a real keyword-overlap search runs against past decisions that already have a recorded outcome, surfacing what happened last time something similar was tried.

3

Review reminder fires

On the decision's real review date, a scheduled sweep notifies the decision-maker to come back -- it never guesses or auto-fills an outcome, only prompts a human to record one.

4

Outcome recorded

What actually happened is logged and rated Good/Mixed/Bad, permanently closing the loop on that specific decision.

5

Calibration computed

Average stated confidence is broken down by real outcome rating -- well-calibrated judgment shows higher confidence on Good outcomes than Bad ones; if the numbers are close, stated confidence isn't tracking reality.

Getting Started

  1. 1Enable Decision Ledger from the Module Marketplace
  2. 2Log a decision with a review date that matches when its outcome will actually be knowable -- there's no value in reviewing before that
  3. 3Come back on the review date (or whenever the notification arrives) and record what really happened -- the calibration summary is only ever as good as the outcomes people actually record

Works Well With

AI Studio

AI content generation, inside the platform.

AI Assistant

A chat-based assistant that knows your business.

Manager Copilot

Idle alerts filtered against real recent activity.

Business Brain

Retrieval over your own business memory and knowledge base.

Need help implementing Decision Ledger?

Enterprise deployment, workflow design, and data migration — talk to the team that builds it.

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