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I’ve just completed Invoice Manager — a production-ready Windows desktop application built with .NET 10, C#, WPF, MVVM, EF Core and SQLite.
The application covers the full workflow from quotation to payment, including:
• customer and service management
• quotations and invoices
• quote-to-invoice conversion
• partial and full payments
• PDF generation
• dashboard reporting
• historical document snapshots
• automated testing and CI
The project was built with Clean Architecture and includes 97 automated tests, a self-contained Windows release, technical documentation and architecture decisions.
This project gave me a chance to work not only on the UI, but also on business rules, persistence, transactional workflows, testing and release engineering.
#dotnet #csharp #wpf #softwaredevelopment #desktopapp #cleanarchitecture
github.com
GitHub - Staniek-Tech-NL/invoice-manager: Local-first quotation and invoicing application for Windows built with .NET 10, WPF and Clean Architecture.
Local-first quotation and invoicing application for Windows built with .NET 10, WPF and Clean Architecture. - Staniek-Tech-NL/invoice-manager
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Really clean and polished app design! The booking flow looks intuitive and the overall UI feels modern and easy to use. 👏
good work
→ Live demo: https://lnkd.in/gmc44Jc5
Most “AI document tools” are just OCR with a chat box.
Your team still re-keys the PDF.
Your manager still can’t approve without opening 12 tabs.
Your audit trail still lives in someone’s inbox.
That’s not intelligence.
That’s expensive busywork wearing a demo costume.
We built DocFlow differently:
Ingest → Validate → Decide → Export
Humans only touch exceptions.
Every step leaves an audit trail.
One document engine.
Six industry workflows:
Finance · Procurement · Compliance · Legal · Healthcare · HR
Not a deck. A live console.
Open it. Clear one real exception in under 2 minutes.
Then tell me I’m wrong in the comments.
If you’re building AI ops / document workflows for your company — message me.
We ship the product UI + the workflow loop.
♻️ Repost if your AP / ops team is drowning in PDFs.
💬 What’s broken in your document process right now?
#AI #ArtificialIntelligence #SaaS #B2BSaaS #Startup #Entrepreneurship #ProductDesign #UXDesign #FinTech #Operations #DigitalTransformation #Automation #MachineLearning #DocumentAI #AIOps #AccountsPayable #Procurement #Compliance #FutureOfWork #Innovation
Accounts payable is one of those jobs where the work is dull and the mistakes are expensive. Someone types the invoice in, checks it against the purchase order, chases the right person for approval, and posts it before the terms run out. Do that a thousand times a month and something slips: a duplicate payment, a missed early payment discount, a unit price that quietly went up in March.
So I built Ledgerpilot, an accounts payable system that handles the routine invoices end to end and asks for a person only when it should.
An invoice arrives by email, supplier portal or EDI. The system reads it, checks every line against the purchase order and the delivery note, looks for duplicates across the last six months, then applies the company rules before it goes into the accounting system.
Three things I cared about while building it.
The person gets evidence, not a verdict. When an invoice needs review, the screen shows the scanned document with every field the AI read marked on it, how sure it was about each one, the line by line comparison against the order, and a note on what it recommends and why.
Policy comes before confidence. Rules like "over $10,000 goes to the controller" or "new supplier, first three invoices" run first. A confident read never lets an invoice skip the person who is supposed to sign it.
You can change the rules and see the effect before you save. Move a threshold and the screen tells you how many of the last 30 days of invoices would have gone through on their own.
The front end is React and TypeScript. The backend is designed around .NET and Node.js services, RabbitMQ, PostgreSQL and AWS, with queue depth, worker health and cost per document visible in the app.
I built this as a portfolio project with realistic sample data, not a client system, so the thinking is mine to show: the flow, the screens and the checks around the AI.
If your finance team is buried in invoices and you want automation your auditor will be happy with too, I am glad to talk it through.
It runs 23 characters over 2,000. Cut the words "and the mistakes are expensive" from the first line and it lands at 1,993. I left it in because it earns its place in the hook, and most feeds allow more than 2,000.
