惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

宝玉的分享
宝玉的分享
小众软件
小众软件
J
Java Code Geeks
I
InfoQ
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
腾讯CDC
L
LangChain Blog
博客园 - 司徒正美
量子位
Y
Y Combinator Blog
C
Check Point Blog
T
Tailwind CSS Blog
D
DataBreaches.Net
Blog — PlanetScale
Blog — PlanetScale
N
Netflix TechBlog - Medium
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
F
Fortinet All Blogs
云风的 BLOG
云风的 BLOG
A
About on SuperTechFans
B
Blog RSS Feed
酷 壳 – CoolShell
酷 壳 – CoolShell
大猫的无限游戏
大猫的无限游戏
V
V2EX
阮一峰的网络日志
阮一峰的网络日志

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
Local AI Office Assistant That Never Sends Your Documents...
saritha vode · 2026-05-26 · via DEV Community

saritha vodela

I Built a Local AI Office Assistant That Never Sends Your Documents to the Cloud

Most AI document tools today have one thing in common:

Your files leave your computer.

Invoices, contracts, receipts, meeting notes, customer documents — everything gets uploaded somewhere.

I wanted something different.

So I built a local AI-powered Office Assistant for Windows that runs directly on your machine using Gemma 4 through Ollama.

No subscriptions. No API keys. No cloud processing.


Why I Built It

I kept running into repetitive document tasks such as:

  • Summarizing PDFs
  • Extracting information from receipts
  • Converting one document type into another
  • Pulling action items from meeting notes
  • Creating invoices from timesheets

The process was repetitive and often involved copying sensitive files into online tools.

I wanted a system where files stay on the user's machine.


What the App Can Do

📄 Bill Summation

Upload:

  • Receipt photos
  • Scanned invoices
  • JPG/PNG files
  • Excel spreadsheets

The AI reads:

  • Vendor names
  • Dates
  • Line items
  • Totals

Once processing is complete:

✅ Review extracted information

✅ Correct any data if needed

✅ Save formatted Excel files

✅ Generate a Master Total spreadsheet with linked bills and totals

Useful for:

  • Expense reports
  • Monthly accounting
  • Supplier reconciliation

💬 Ask My Document

Load almost any document:

  • PDF
  • Word
  • Excel
  • Text files
  • Images

Then ask questions in plain English:

Examples:

Give me a 100-word summary

Extract all phone numbers

Draft a professional response

List all action items

The original document is never modified.


✨ Transform Documents

Convert documents into entirely different formats:

Examples:

  • Timesheet → Invoice
  • CV → Cover Letter
  • Meeting Notes → Structured Minutes
  • Letter → Professional Reply

Supports:

  • Custom instructions
  • Template-based formatting
  • Single file processing
  • Batch folder processing

Features

  • Completely local processing
  • No cloud upload required
  • Gemma 4 AI via Ollama
  • Batch processing
  • Email notifications
  • Configurable output folders
  • Custom templates
  • Debug logs
  • Professional Excel outputs
  • PDF support

Things I Learned Building It

Building local AI turned out to be very different from using cloud APIs.

Challenges included:

  • OCR accuracy
  • Memory management
  • Model selection
  • Performance optimization
  • Handling large document workflows

A GPU definitely helps, but smaller Gemma models can still work on modest hardware.


What Makes It Different

Many AI tools focus on convenience.

I wanted to focus on privacy too.

This means:

  • Documents never leave your machine
  • No recurring subscriptions
  • No API keys
  • No external servers involved

I think local AI is going to become a larger part of everyday productivity workflows.


Interested?

I'm currently looking for feedback and early users.

If you'd like to try it, leave a comment or send me a message and I'll send you a download link.

I'd also love to know:

What repetitive document task would you automate first?

Thanks for reading.