Local & private AI for data-extraction
Pulling structured fields and tables out of messy documents with local models. Narrow, verifiable and token-heavy work, which makes it a good fit for local AI.
Rebel BitesExtracting clean data from old SEC filings with small models
7B-13B models running locally turn wordy 1990s SEC text filings into structured tables, about 97% accurate on a random sample. Lots of tiny prompts, because tokens are free.
Offline LLM on a Raspberry Pi 5 for classification and extraction
Phi-3 mini at Q4_K_M runs at 4-6 tokens per second on an 8 GB Pi 5 with no network at all. Under GDPR, data that never leaves the board isn't transferred anywhere.