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Saw your demo video. Are you focusing on the finance sector primarily? It is a challenging industry IMO, requiring high accuracy and has strict privacy/security bar. How do you address these concerns?

Curious what are the biggest complain from your users? Are they willing to manually auditing the numbers in the table, make sure the output is 1. accurate. 2. formatted in the table they expected.

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We have seen a lot of use cases in finance and are currently working with a few firms. Accuracy is generally their primary requirement. We've been focusing on not just accuracy but also the audit experience which includes confidence scoring. Your right about security and we are currently undergoing a soc 2 audit.

Generally firms are outsourcing the data entry and are already manually auditing with shortcuts like summing values.

Relating to formatted in the table they expected. We extract the data directly into their template format so it is always in the table they expect.

I've been working on some ML solutions similar to this with, and the high accuracy is the challenging part. Specially with "creative" layout documents.

I'm curious as well to see how they are handling accuracy, since I had to build an external agent to validate data.

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