https://github.com/mizcausevic-dev/decision-memory-engine
Python FastAPI decision engine for storing prior decisions, rationale, confidence, stale assumptions, and operator context recovery.
https://github.com/mizcausevic-dev/decision-memory-engine
analytics backend context-engineering decision-intelligence fastapi memory-systems operator-workflows portfolio python strategy
Last synced: 3 days ago
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Python FastAPI decision engine for storing prior decisions, rationale, confidence, stale assumptions, and operator context recovery.
- Host: GitHub
- URL: https://github.com/mizcausevic-dev/decision-memory-engine
- Owner: mizcausevic-dev
- Created: 2026-05-15T15:59:57.000Z (20 days ago)
- Default Branch: main
- Last Pushed: 2026-05-17T05:12:43.000Z (18 days ago)
- Last Synced: 2026-05-17T07:26:40.033Z (18 days ago)
- Topics: analytics, backend, context-engineering, decision-intelligence, fastapi, memory-systems, operator-workflows, portfolio, python, strategy
- Language: HTML
- Homepage: https://kineticgain.com/
- Size: 1.24 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
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README
# Decision Memory Engine
Python and FastAPI decision-intelligence service for **storing prior decisions, rationale, confidence, stale assumptions, and operator context recovery**.
> **What this repo proves**
>
> Teams make better follow-on decisions when they can recover the original rationale chain instead of only inheriting the headline outcome.
## Why this repo exists
Organizations often remember what was decided but lose the more valuable parts:
- which assumptions made the decision safe
- which sources supported the decision
- when the reasoning should be reviewed again
- what changed after the decision was made
`decision-memory-engine` turns those decision artifacts into reusable memory
records. It helps teams decide whether an old decision is still safe to reuse in
a new board, product, risk, or operator context.
## Screenshots
### Overview
### Memory Board
### Replay
### API Summary
## What it includes
- FastAPI service for decision memory and context replay
- sample decisions across revenue, risk, platform, real estate, and education lanes
- rationale, stale-signal, and next-review tracking
- owner-lane and replay surfaces
- HTML proof scenes and PNG screenshots generated from the repo
- tests, docs, changelog, and CI
## Local run
```powershell
cd decision-memory-engine
py -3.11 -m venv .venv
.\.venv\Scripts\python.exe -m pip install -r requirements.txt
.\.venv\Scripts\python.exe -m app.main
```
Open:
- [http://127.0.0.1:5006/](http://127.0.0.1:5006/)
- [http://127.0.0.1:5006/memory-board](http://127.0.0.1:5006/memory-board)
- [http://127.0.0.1:5006/replay](http://127.0.0.1:5006/replay)
- [http://127.0.0.1:5006/owners](http://127.0.0.1:5006/owners)
- [http://127.0.0.1:5006/docs](http://127.0.0.1:5006/docs)
If that port is occupied:
```powershell
$env:PORT = "5010"
.\.venv\Scripts\python.exe -m app.main
```
## Validation
```powershell
cd decision-memory-engine
.\.venv\Scripts\python.exe -m unittest discover -s tests
.\.venv\Scripts\python.exe scripts\run_demo.py
.\.venv\Scripts\python.exe scripts\smoke_check.py
.\.venv\Scripts\python.exe scripts\render_readme_assets.py
```
## API routes
- `GET /api/dashboard/summary`
- `GET /api/decisions`
- `GET /api/decisions/{decision_id}`
- `GET /api/timeline`
- `GET /api/owners`
- `GET /api/sample`
- `POST /api/analyze/recollection`
## Architecture
```mermaid
flowchart LR
A["Decision records"] --> B["Decision memory service"]
B --> C["Owner lanes"]
B --> D["Replay and recollection scoring"]
B --> E["Operator HTML surfaces"]
D --> F["Briefing-safe reuse decisions"]
```
More detail lives in [docs/architecture.md](./docs/architecture.md).