Many customers have asked me about AI offerings, and I am considering them. While this is doable with modern LLM technologies, I need to consider many issues.
The first is that nobody, myself included, likes their data being part of someone else's machine-learning training pipeline. That's why I promised my users that I wouldn't use their data for machine learning training without asking for explicit consent (and, of course, anonymization will be needed).
While I know everything involved in AI sounds cool, do we really need LLM for a task like this? Maybe a rule-based import engine could kill 95% of the repeating transactions? And that's why I built beanhub-import[1] in the first place. Then, here comes another question: Should I make LLM generate the rule for you or generate the final transactions directly?
Yet another question is, everybody/every company's book is different from one to another. Even if you can train a big model to deal with the most common approaches, the outcome may not be what you really need. So, I am thinking about possibly using your own Git history as a source of training data to teach machine learning models to generate transactions like you would do. That would be yet another interesting blog post, I guess if I actually built a prototype or really made it a feature for BeanHub. But for now, it's still an idea.
Many customers have asked me about AI offerings, and I am considering them. While this is doable with modern LLM technologies, I need to consider many issues.
The first is that nobody, myself included, likes their data being part of someone else's machine-learning training pipeline. That's why I promised my users that I wouldn't use their data for machine learning training without asking for explicit consent (and, of course, anonymization will be needed).
While I know everything involved in AI sounds cool, do we really need LLM for a task like this? Maybe a rule-based import engine could kill 95% of the repeating transactions? And that's why I built beanhub-import[1] in the first place. Then, here comes another question: Should I make LLM generate the rule for you or generate the final transactions directly?
Yet another question is, everybody/every company's book is different from one to another. Even if you can train a big model to deal with the most common approaches, the outcome may not be what you really need. So, I am thinking about possibly using your own Git history as a source of training data to teach machine learning models to generate transactions like you would do. That would be yet another interesting blog post, I guess if I actually built a prototype or really made it a feature for BeanHub. But for now, it's still an idea.
[1]: https://beanhub-import-docs.beanhub.io/