Hi there,
Thank you very much for updating the GnuCash ML policy to grant me the opportunity to introduce my tool. I would like to briefly introduce "Tensor-Link Utility (TLU)", an open-source tool I have developed: https://github.com/renpoo/TLU Imagine a small business keeping their daily books in GnuCash. What if they could mathematically analyze their ledger to identify systemic strengths, weaknesses, and leverage points? For instance, discovering that "prioritizing accounts receivable cycle optimization or cost of goods sold yields much higher leverage than cutting operating expenses." TLU makes this possible by treating double-entry bookkeeping data as a directed graph (flows between accounts). The usage is simple: 1. Export your general ledger or journal from GnuCash to a .csv file. 2. Map the "Date", "Source Account", "Target Account", and "Amount" columns in the configuration file. 3. Run the TLU batch processor. TLU analyzes the transactions through the lens of graph theory adjacency matrices, borrowing concepts from physics and mathematics—such as thermodynamics (entropy/free energy dissipation) and control theory (LQR sensitivity). By feeding the output data and plots to an LLM along with the provided analysis guidelines, you can decipher non-obvious business insights. It allows you to transition from simple multi-dimensional ledger comparisons to a dynamic physical interpretation of your capital flow, while simultaneously flagging anomalies (such as circular transaction loops or leaks). If you are interested, please check out the repository. I would love to hear your feedback on my GitHub repository. Best Regards, Renpoo (Kow) # R # # A O # ☆—— 月岡 蓮風 （TSUKIOKA, Renpoo）————— # T # _______________________________________________ gnucash-user mailing list [email protected] To update your subscription preferences or to unsubscribe: https://lists.gnucash.org/mailman/listinfo/gnucash-user ----- Please remember to CC this list on all your replies. You can do this by using Reply-To-List or Reply-All.
