Why We Added Manual Data Entry to GLYNT

Manual Data Entry is the Glidepath to Automation

The title of this article draws a sharp contrast: Manual Data entry and AI. GLYNT is a powerful AI-based data extraction service, providing data from utility bills at high rates of accuracy (98%) after training on just a handful of sample bills. With this leading technology, and the hyper-efficiency of AI, why did we open up GLYNT to manual data entry? The answer reveals much about the current state of customer acceptance of AI.

First, some stats. Surveys show that more than 80% of SMB managers and more than 70% of sales reps do some data entry work each day (1)(2). Bill.com estimates that over 80% of business payments each year involve a paper check (3). In sum, there is a lot of paper and a lot of manual data entry sprinkled around every office. Given that so many people are already doing a bit of manual data entry, adding a product feature that makes data entry easier makes sense. But we added more: Manual Data Entry is now the glidepath to automation.

Since GLYNT’s launch we’ve noticed keen interest in our product…and a lack of trust. Everyone hopes GLYNT will work for their needs, but have been disappointed with product promises before (or has a boss who had that experience). For GLYNT it is a case of “prove it on my bills.” So we opened up Free Trials. But that was not enough.

So we added Review mode on GLYNT, making it easy for the user to directly compare the data extracted by GLYNT to what was printed on the bill. The visual confirmation creates a level of transparency that most AI lacks. Our users love Review mode because it gives them control over the output of GLYNT in a fast and easy way, something not provided by outsourced manual data entry teams or legacy technologies. But this also was not enough.

We heard loud and clear from our users that the GLYNT UI was super-easy to use. GLYNT needs only 20 bills from a utility to train a model; 7 bills are used training, and 13 are the holdout set, the initial data extraction. (Yes, GLYNT provides results in the first 20 utility bills.)

Our customers typically have lots of incoming utility bills to process each month, but also quite a few that dribble in, such as 3 – 4 water bills from the City of XXX. They want to use GLYNT to setup the field names, enter the data and download it in CSV file format. GLYNT’s simple UI makes this fast and easy.  Ironically, they want to use an AI-powered tool for manual data entry 🙂

So we added this feature, Manual Data Entry. But with GLYNT, the days of manual data entry are numbered. Let’s go back to those 3 -4 water bills. In the first and second months, the user uses Manual Data Entry to put the bills into GLYNT’s system. But by the third month the bills have accumulated and GLYNT can be trained. In the fourth month data is extracted automatically.

In sum, we put a simple product feature, Manual Data Entry, in the users’ hands. Users get a first and immediate benefit, a simple way to get clean labeled data. But at the same time, Manual Data Entry is the glidepath to data automation.  No change in work habits, no heavy software to install. GLYNT just slips right in and delivers clean, labeled automated data after a few bills have passed through the system.

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GLYNT

Extract data from any residential or commercial utility bill. Choose your fields. Any utility

SNAP

Get data from residential utility bills instantly. Consumer uploads pdf or scans. Standard field list

LINK

National platform for utility connections. Fetch all historical bills and interval data. Quick automated retrieval


RESIDENTIAL

Increase sales with SNAP and LINK. Fast utility bill data for customized proposals and product offers

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Speed proposal development with GLYNT’s automated data extraction. A solution for bulk bills too


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Use GLYNT to extract the fields you select from residential and commercial bills. Any data, any utility

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Get instant data from residential utility bills. Standard field list

LINK

Fetch utility bills and interval data. User provides online credentials


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