Appreciate the feedback. There's also a connected mode leveraging Plaid where transactions pass through servers memory and never stored. Outside the US, CSV is the only path for now otherwise agree CSV export is a chore for multi-bank users.
"if you're having to pull in data from multiple different sources, each with their own flow for exporting"
you say this, but i got ChatGpt to just open chrome logged into two credit cards and a bank app and download everything with a certain criteria (i did this to populate items in a travel split app). So maybe it's not that bad
Very cool. What does it use the model for? Could you replace it with something lighter, like some classifiers[0]? Or do you need the chat? Besides the chat, what other tasks is the model used for? Thank you!
I use budgeting apps on a daily basis, and I'll just share my personal feedback: I'm absolutely not downloading ~3 gigs for a budget app. Everything I need to "ask" the app is already available to me in the form of reports, charts, and tables. I don't really have many open-ended questions about my budget because anything important to track is already handled deterministically.
Also yes, it's local but the data you're importing is already with a private organization on the cloud. In that sense, having a local copy of it does not really do anything for me in terms of privacy etc.
As I said, I use budgeting apps daily (one for personal use (self-made), another for business (very old freenium era software that has not failed me in the last 5+ years of self-hosting it)) and I do not see any need for generative AI in that workflow from my pov. YMMV
I love the idea of local only apps woth no network comms. I do wish macOS had some way you could enforce that out of the box though. Rather than trust the claims of the developer.
Another app I love that does the same. Queryable which lets you natural language search your photos on device on iOS and predates most of the current AI craze (2022) and also apple adding this themselves to photos:
https://queryable.app/
Indeed, macOS only blocks incoming traffic. For this app and in "local mode", there are only two kinds of requests: one to download the models from HF and an optional version check that sends nothing about the user and can be turned off. A simple test, once you download, try turning off your wifi and use the app.
you only need 2 sections. an above the fold area and something below the fold. simple.
thanks for making this. “its
private” is not a selling point, whats other differentiators does it have? really the AI analysis and potential agentic aspect right?
you could point out that it doesnt use data centers or harm the environment without explaining how or what that means upfront
Feedback: manually categorizing transactions is a common and tedious task. Your 'for review' transaction list shows the category, but it's not editable. To review and fix the category, you must:
- read the category
- click on the '...' button at the end of the line (not near the thing you want to correct, and not my first guess for settings the category)
- this creates a popup
- mouse into the popup and click on the dropdown for setting the category.
Just have the category label in the list clickable, to show the category dropdown.
It saves one click, two mouse movements, and having to figure out that '...' is the action you need to fix a category.
Plaid is the main risk - if they were hacked, that's way worse than a log of my AI queries. What's exciting with LLMs is the possibility to do classification much better.
I gave it a go and imported a transaction CSV from my bank - National Australia Bank. 150 row CSV. The Description import column was assigned to the Merchant Name CSV column (the Merchant import column was also assigned to this CSV column) and as a result 25 rows were going to be ignored. Here's the CSV header row:
Date,Amount,Account Number,,Transaction Type,Transaction Details,Balance,Category,Merchant Name,Processed On
Hand-picking the Description column to be assigned to the details column sorted it out; not sure how you're auto-selecting column mappings but maybe 'details' should be recognised as closer to 'description' than 'merchant name' is.
You have a free budgeting app for Mac? Can you have as an app so I can download it in my iPhone? Can Pulse Local connect to my bank app and automatically records my spendings?
Also am curious about your reasoning behind usage of Qwen3.0 model as well!
after a “not sure,” how often does reprhasing get a correct answer on the next try/do users give up? retries could make a simple lookup surprisingly slow?
Great question and in all honesty, real users just started downloading the app today so I don't have any idea yet on how often a rephrased question succeeded. That being said, a retry costs about 12 to 14 seconds with the checker against 1/10th of a second without so it doubles the wait. What I've tested was that with the checker, even though fewer questions get an answer (about 47% right against 60% without), wrong answers fell to 5 in a sample of 494 questions (compared to 100 wrong without the check). Conversations are hit the most from the moment it answers "not sure" so nothing to build on for the next question. I've also given users the option to switch off the checker for speed. I still have many ideas to try and hopefully I keep improving trade-offs.
curious what ppl actually come back for after the first few days. do they keep asking questions about their spending? feels like a lot of the useful stuff would be things they wouldn't think to ask about
In all honesty, I don't know what would bring people back since I just launched but a few things the app does unprompted: patterns it finds in spending (insights), money and cash flow, forecast, as for the chat there are always a few suggested questions so you don't always need to know what to ask. But agree, it would be great to hear what returning users actually do.
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[ 0.28 ms ] story [ 23.5 ms ] threadIt also requires you generally to trust some third party with your data.
Here’s an API one for Australia / New Zealand / USA: https://redbark.com/developers
you say this, but i got ChatGpt to just open chrome logged into two credit cards and a bank app and download everything with a certain criteria (i did this to populate items in a travel split app). So maybe it's not that bad
0: https://jeffyclassify.com/blog/when-llms-fail-at-classificat...
Still it could be handy to be able to do that locally, maybe model tweaks could be shared back upstream.
The bridge between deterministic accounting principles to non-deterministic patterns trying to simulate it at will is a pretty big thing to cover.
Also yes, it's local but the data you're importing is already with a private organization on the cloud. In that sense, having a local copy of it does not really do anything for me in terms of privacy etc.
As I said, I use budgeting apps daily (one for personal use (self-made), another for business (very old freenium era software that has not failed me in the last 5+ years of self-hosting it)) and I do not see any need for generative AI in that workflow from my pov. YMMV
Another app I love that does the same. Queryable which lets you natural language search your photos on device on iOS and predates most of the current AI craze (2022) and also apple adding this themselves to photos: https://queryable.app/
https://github.com/objective-see/lulu
[0]https://fastino.ai/blog/fastino-nemotron-3-5-lightning-finan...
you only need 2 sections. an above the fold area and something below the fold. simple.
thanks for making this. “its private” is not a selling point, whats other differentiators does it have? really the AI analysis and potential agentic aspect right?
you could point out that it doesnt use data centers or harm the environment without explaining how or what that means upfront
- read the category
- click on the '...' button at the end of the line (not near the thing you want to correct, and not my first guess for settings the category)
- this creates a popup
- mouse into the popup and click on the dropdown for setting the category.
Just have the category label in the list clickable, to show the category dropdown.
It saves one click, two mouse movements, and having to figure out that '...' is the action you need to fix a category.
Also am curious about your reasoning behind usage of Qwen3.0 model as well!