Captricity was able to extract the information from the 30,000 forms in about a week (compared to the months it would have taken with manual entry). “Captricity was very quick and flexible. We were able to tweak the forms and extract the data we needed to complete our research quickly and efficiently. One feature that has been particularly useful is the ability to click on a cell and view the original data,” said Suri. The team expects to have access to a lot more data for this research project and Captricity will be ready to help again.
Innovation on the product end led the company to think about how to innovate throughout the customer lifecycle (particularly the manual and error-prone order entry step). BRAX partnered with Captricity to streamline the process—doing away with manual data entry almost entirely. Thousands of individual records are now consolidated into one order without a customer needing to perform a single keystroke of data entry. The data from Captricity also flows into the BRAX CRM system for enhanced order processing visibility and tracking to create one smooth order management process.
Scott is happy to have been able to reduce processing cost by reallocating those 400 employee-hours while increasing service to Catapult’s customers. Using Captricity’s reliable data capture technology and Salesforce integration, Catapult has cut the time it takes to close the loop with sites visited in half. These timely and detailed summaries sent to employers set Catapult apart from its competitors. The timeliness and scalability of that reporting, enabled in part by the introduction of Captricity, is a driving force behind Catapult’s tremendous growth.
Captricity’s powerful web-based data extraction platform combines machine learning algorithms and human workers to ensure more than 99 percent accuracy for most data—even handwriting. Captricity’s tight integration with Salesforce and use-what-you-need pricing model was an ideal fit for Integra. In addition, the platform enables Integra to quickly and easily set up multiple templates that match the formats used by the providers submitting orders and authorizations.
Captricity’s web-based platform enabled the SEIU to scan forms on site as they received them. The system’s capacity to achieve almost perfect accuracy—even with the handwritten data—was a critical decision point. The ability to quickly and easily define the fields for extraction and perform rapid review of the results was another key decision point for the team. “My first instinct was to go paperless, but that does not work for this population. Using a paper form is not as sexy, but it works. A tool like Captricity makes a big difference,” concluded Ruparatne.
In the context of government data, privacy is a critical concern. Captricity is designed to manage confidential information, and is built with state-of-the-art security fully integrated into every step of the data digitization process. Our unique approach to privacy ensures the protection of sensitive data. Capticity’s ability to securely capture data from static documents of all types— including handwriting—at a 99+ percent accuracy rate makes it ideal for government organizations.
Chief Health Informatics Officer, CTO, and Director, Office of Informatics and Tech Innovation
on its website as well as the QR card students can call up on their cellphones. In this way, the college is collecting consistent data from multiple touch points, enabling recruiters to serve many different constituents and event types effectively. “Even if the accuracy rate were 50 percent, it would still be better than what we have. With Captricity, we are seeing 90 to 95 percent accuracy rates. The only time we see any issues is when the handwriting is really indistinct. Even with students writing in longhand, the accuracy rate is quite high,” said Gayle.
The Commission needed a cost-effective solution that could integrate with an eFax system, accurately extract data from handwritten forms and integrate that data into the existing eFiling system. They tried using several OCR systems and the results were far below the level of accuracy they required, particularly with handwriting. With time running out, the team was growing concerned.
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