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From my build archivePrototype / design pivot

BackPocket OS AI

Local-first AI operations assistant prototype for small-business admin workflows, focused on email triage, quotes, records, and human-approved actions.

01

Why I started it

Small businesses lose time across quotes, invoices, Gmail follow-ups, job notes, payments, documents, and lead tracking.

Generic AI assistants are too disconnected from the operational workflow and too risky if they act without review.

02

What took shape

A local-first assistant direction where Pip can draft, classify, and organize work while the operator approves outbound or destructive actions.

Backend workflow direction around FastAPI, local storage, Gmail/Drive-style integrations, and structured business records.

A product pivot toward offline-first ownership, privacy, and human-in-the-loop review instead of a generic cloud chatbot.

03

Under the hood

Email triage pipeline direction for classify, draft, approve, send/archive, and notify.

Local-first storage direction using SQLite first, with a self-hosted PostgreSQL path later.

AI fallback strategy across local Ollama, hosted model fallback, and Gemini.

Workflow modeling for leads, quotes, invoices, payments, job files, ABN/GST checks, and document search.

RAG/document intelligence direction for retrieving relevant business context before drafting.

04

Where it stands

Prototype / design pivot. This page avoids production, revenue, uptime, or usage claims until they are verified.

05

Repo notes

Primary language: Python

Technologies: Python, FastAPI, Flutter, SQLite, Gmail, Ollama, Gemini, RAG, Docker, Dart, HTML, JavaScript, Kotlin, CSS, C++, Shell, CMake, Batchfile, PowerShell, Swift, C, VBScript, Objective C, Uvicorn, Pydantic, Docker Compose, GitHub Actions

Topics: Not specified

Last updated: 2026-09-18T10:51:35Z

Stars: 0

Forks: 0

Status: Active

Visual notes

What the build looked like.

Read the longer notes
I have not added screenshots to this entry yet. The original README is still below if you want the less-polished version of the story.

BackPocket OS - Complete Documentation

Welcome to the BackPocket OS documentation hub. This folder contains comprehensive guides for all features, workflows, and system architecture.

šŸ“š Quick Navigation

Core Features

Workflows & Automation

Setup & Configuration

System Architecture

Troubleshooting


šŸ‘„ Team Setup (new contributors — marketing, law, research, engineering)

One-time setup, takes ~2 minutes:

git clone https://github.com/Sharv619/backpocket-mvp.git
cd backpocket-mvp
npm run setup

That installs MCP dependencies, creates the shared knowledge-bank table, and wires up the git hook that auto-logs every merge into main for audit (signed with your git author + commit SHA).

Then open OpenCode in the repo. Four MCP servers load automatically from .mcp.json:

ServerToolsUse for
backpocket-leadssearch / get / create leadsLead intake work
backpocket-quotescreate quote, templates, overdue listQuoting + follow-ups
backpocket-pipelinepipeline summary, record paymentOps / reporting
backpocket-knowledgesave / search / list notesShared team knowledge bank

Rule of thumb: anything worth referencing later — marketing copy, legal notes, research findings — drop it via the save_note tool in the knowledge bank, or just merge it into main and the post-merge hook captures it for you. Every entry is signed with your git identity so audits are trivial.

Full restructure rationale: docs/MCP_RESTRUCTURE_PLAN.md.


šŸš€ Getting Started

1. Prerequisites

  • Python 3.8+
  • Google Cloud Project with APIs enabled
  • OpenRouter API key
  • Gmail OAuth configured

2. Quick Start

cd /home/lade/Hackathons/.git/backpocket-mvp
python3 -m uvicorn main:app --host 127.0.0.1 --port 8000

Visit: http://127.0.0.1:8000/static/index.html

3. Configure Your Sheet

  1. Go to .env and find SPREADSHEET_ID
  2. Copy your Google Sheet ID from the URL
  3. Paste into the .env file
  4. Restart the server

🧠 The Three Twins (AI Agents)

BackPocket uses three specialized AI agents that learn from your feedback:

TwinPurposeBest For
AccountantFinancial & TaxInvoices, GST, BAS, expense tracking
AuditorCompliance & QADocument review, verification, checks
AdminOperations & WorkflowEmail triage, scheduling, reminders

Each twin:

  • āœ… Learns from corrections (builds patterns)
  • āœ… Accesses historical context via RAG
  • āœ… Routes to cost-optimal AI model
  • āœ… Generates professional responses

šŸ’° Cost Optimization

BackPocket intelligently routes API calls to minimize costs:

  • Simple emails → Template (free)
  • Medium complexity → Ollama/local (free)
  • Complex requests → OpenRouter (pay-per-use, but ~80% cheaper than raw API calls)

See AI Models & Routing for details.


šŸ“– Key Concepts

RAG (Retrieval-Augmented Generation)

  • Stores documents in ChromaDB vector database
  • Retrieves relevant context before generating responses
  • Enables AI to reference your business data

Learned Patterns

  • Each correction becomes a learned pattern
  • System automatically applies patterns to similar future emails
  • Over time, twins get smarter without additional training

Vision Processing

  • Analyze invoices, receipts, and documents
  • Extract structured data from images
  • Uses free OpenRouter vision models

šŸ”§ Common Tasks

Import Real Emails

python3 import_real_emails.py

Fetches your actual Gmail messages and populates the dashboard.

Sync Google Drive

Via the Dashboard:

  1. Go to šŸ“ DRIVE section
  2. Enter your folder ID
  3. Click "Sync to RAG"

Or via API:

curl -X POST http://127.0.0.1:8000/api/drive/sync-to-rag \
  -H "Content-Type: application/json" \
  -d '{"folder_id":"YOUR_FOLDER_ID","twin_type":"admin"}'

Generate Blog Post

curl http://127.0.0.1:8000/api/blog/generate?title=My%20Story&theme=entrepreneurship

šŸ“ž Support

For detailed information on any topic, see the relevant documentation file in this folder.

Need help? Check TROUBLESHOOTING.md

Next conversation

Let's make the next system less fragile.

Open to software engineering roles across full-stack systems, platform and reliability work, workflow automation, and applied AI. I value teams where I can keep learning while contributing to real systems and clear delivery outcomes.

Also open to freelance or contract work across full-stack builds, practical automation, technical SEO, and cloud delivery.