In the last month, we released new quality scores for extractions, enabled extracting large tables with the NLP Table method, and made advanced LLM prompt configuration options available in the Sensible Instruct editor for the List and Table methods.

In the last month, we introduced new traceability for the LLM-powered Query method by highlighting the source text for the LLM's answer in the document, made advanced LLM prompt configuration options available in the Sensible Instruct editor for the Query method, made filtering past extractions available in the app and API, and released a new preprocessor for handling page-rotation edge cases.

In the last month, we released new advanced prompt configuration options for methods powered by large-language models (LLMs), introduced confidence signals as a more nuanced alternative to confidence scores for data extracted by LLMs, and made several improvements to existing features.

In the last month, we released improvements to NLP methods, to the SenseML and Sensible Instruct editors, and to API key configurability and security. We added the ability to extract from portfolios in the Sensible app's quick extract tab.

In the last month, we released a new API for classifying a document by its user-defined type, improvements to the Zapier-Sensible integration, to the quick extraction tab in the Sensible app, and to natural-languages methods.

In the last month, we released a powerful new extraction tool powered by large-language models (LLMs), including GPT-4. We also released a new natural-language method, List, and several improvements to existing features.

In the last month, Sensible released GPT-3-powered natural-language methods to capture tables and get answers from documents. We also completely overhauled our web app's design for better navigation, improved several existing features, and added advanced configurability for text tables and types.

In the last month, we introduced the ability to convert document extractions to CSV and the ability to validate the quality of extracted OCR text using confidence scores.

In the last month, we introduced a powerful new way to ask a simple question about data in a document and get back an NLP-powered answer, and added the ability to combine multiple document extractions into one Excel spreadsheet. We also improved OCR preprocessors, and made SenseML syntax more concise for a few NLP methods.

In the last month, we released several feature improvements, including the ability to add instructions to the Summarizer method and the ability to extract from TIFF documents. We also added guided onboarding experiences to the Sensible app.