romanleeb

smart

Hey HN,

I built Billpal because every tool I tried wanted to turn me into an accountant.

I'm self-employed, I don't need much – no P&L, no balance sheet. Happy to pay a CPA for this and to file my taxes.

But I also didn't want to do bookkeeping myself either. It's a stupid task.

Was genuinely surprised how little automation these accounting tools have. Even when I upload a receipt, I still have to type most of the fields by hand.

So I built my own thing: grab invoices from my inbox, parse them, and match each one to the right bank transaction automatically.

Now all I do is export a CSV and send it to my tax advisor.

Curious what you think. And happy to get into the weeds on the matching logic.

Roman

amazing

Thank you! Well, I built it in a way that the format is kinda universal – expenses are categorized but not with tax codes. Instead I am using labels like e.g. 'Cloud Infra & Hosting'. Plus apart from the basic infos I even extract things like reverse charge y/n or validate VAT IDs to make it as easy as possible for my tax advisor.

So it will not file your taxes for you but it prepares the raw data for your tax guy in a way that they have minimal effort and you can save quite substantially on the bookkeeping part. I'm in Austria and it is a bit cheaper here but also quite costly. Now I only pay for the tax filing, annual accounts and consulting when I need it.

Thanks - we'll do!

I agree with you mostly but not 100%. It's definitely true that the way how you build it makes a product stand out - however the goal of this tool is more to understand WHAT to build as it gives you a glimpse into the opinions customers have about other (similar) products. The how is then onto the devs for sure. Yes you are right if you know for instance Hubspot you do not need this application to tell you stuff about Hubspot you already know, it tells you how the audience perceives the product and the offering.

Data sources are various sites that have detailed reviews on software. We did not fine-tune anything yet as the initial goal is and was to validate the idea per se. We'll improve it further of course once we see there is a need for this.

Very good input, thanks! We'll add some examples on the page.

Currently we have a quite basic RAG setup, no fine-tuning.

We wanted to get this out fast so decided to use Assistants API but definitely needs some polishing in this RAG pipeline (e.g. having more control over the exact search queries). For the MVP it was convenient as it all comes out of the box. Metadata filtering also better with Pinecone for instance.

Precisely, problems/complaints/negative comments unveil a lot of interesting opportunities.

For this very reason we instructed the model to pay a bit more attention to expressions with a negative sentiment.