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OpenEnvoy’s Self-Serve API Saves Finance Teams Time & Resources With State-Of-The-Art Data Extraction

OpenEnvoy, the Bay Area fintech company that created the first real-time AP automation solution, has released the first-of-its-kind Self-Serve AP Automation API. Through state-of-the-art Natural Language Processing (NLP), finance leaders and teams can utilize audit and extraction technology to achieve real-time data insights.

“Teams who have tried to build in-house systems to extract meaningful data understand the pain of setting up OCR and NLP systems. Even with all the building blocks available, it can take several months to build a product ready system,” says Naveen Kumar, CTO at OpenEnvoy. “We have developed our models to learn from the invoice formats to extract data without any templates. The way we are solving the problem is with a combination of AI and augmented AI to provide high-quality data extraction.”

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With customizable extraction capabilities, finance teams have the ability to utilize the solution in a way that fits their needs to create more agile processes and improve decision-making.

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Customize Data Extraction at a Granular Level

With OpenEnvoy’s Self-Serve API, finance leaders and teams can:

  • Expand infrastructure – Maintain current BI tools without disruption through a lightweight exchange to Self-Serve API.
  • Enhance accuracy – Leverage a two-way system for extraction and audit to improve data accuracy and visibility.
  • Customize extraction – Specify the invoice information extracted down to the line item, including due date, banking information, vendor name, pricing, tax rate, etc.
  • Improve accountability – Refresh the API key on-demand to display a timestamp of the last key generated and used for added layers of security.

Finance leaders and teams can maintain established AP infrastructure by connecting to their existing BI systems with Self-Serve API. Teams looking to save time and resources in building an internal extraction system can use Self-Serve API as a white label solution and avoid complex partnership arrangements.

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