Unstructured file types include about 80% of all company data, such as spreadsheets and PDFs. PDFs constitute the de facto standard for corporate knowledge in almost every sector. Every week, dozens of hours are lost because their storage structure is completely unsuitable for usage in digital workflows. It is common practice for businesses to employ conventional methods when developing an extraction pipeline for each unique document layout. That means a lot of time spent training and identifying the model, as well as ongoing maintenance if models malfunction due to changes in design. Also, while off-the-shelf LLMs have great reasoning capabilities, they have problems with hallucinations and inaccurate extraction; thus, they need to be more dependable for industrial use cases.
Meet Reducto, an AI-powered startup that has developed a language model for schema-based extraction. Reducto has constructed vision models to read documents naturally. With the new model’s ability to process much larger documents and its training to reference all sources properly, you can audit and verify its outputs.
The new API Reducto is trying to fix the issue regarding unstructured data. It can turn any unstructured material into structured data using a mix of neural networks and old-school machine learning. Reducto is excited to collaborate with top teams in the insurance, healthcare, and financial industries to enhance the unstructured data intake using our API, which is currently in production life. Structured extraction works across all layouts with best-in-class accuracy, thanks to this new API that takes advantage of all our efforts to improve the document understanding models.
How Reducto works
Reducto finds the important information in an unstructured document by analyzing its content. The data is subsequently extracted and transformed into a structured file, like a CSV or JSON. After that, it’s much easier to examine and put this structured data to use.
Reducto creates a layout segmenting model to identify and catalog all items. Reducto may recompose the document structure while preserving the original content by classifying every text block, table, picture, and figure. This allows us to utilize a specific technique for each. Many steps are involved in each pipeline; however, to summarize Reducto:
Even with nonstandard layouts, accurately extract text and tables.
Make graphs into tabular data and document picture summaries automatically.
Create intelligent chunks of data based on the document’s arrangement.
Speed through lengthy documents with ease.
In Conclusion
With the new API from Reducto, you can easily transform complicated documents and spreadsheets into schema-compatible structured data with no manual tweaking required. Businesses can benefit greatly from using Reducto to extract value from their unstructured data. Reducto helps companies save time money, and get useful insights by automating and streamlining the data extraction process.
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