Many industries that impact our day-to-day lives, including logistics,
manufacturing, financial services, insurance, and government, still run on
paper. These documents contain critical information that powers important
workflows like clearing shipments past customs, processing insurance claims,
underwriting loans, tracking machinery parts, issuing tax refunds, and parsing
clinical lab reports. Unfortunately, document processes still involve people
manually keying in information into digital systems. These labor-intensive
workflows significantly increase the time it takes to extract information,
leading to added costs, poor customer experience, and lack of scalability for
high volumes of documents.
To tackle this challenge, companies previously used technologies like Optical
Character Recognition (OCR). However, OCR solutions only transcribe text
without extracting the most relevant fields. Most “intelligent” extraction
solutions rely on customers to manually define templates or hard-coded sets of
rules to handle data extraction. The rules dictate which part of the document
corresponds to a certain field, which means the system can only process the
document layouts that fit the original template. But, if you change vendors,
document types, or update the document in any way, then you need to manually
define another set of rules. Solutions like these take a lot of upkeep and
result in poor quality when dealing with complicated, variable document types.
Imagine being able to feed any type of document into a system that can quickly
and accurately extract fields and link entities, even from new layouts or
formats — all without any setup or maintenance effort on your end.
Tech-forward companies are recognizing the importance of deploying a robust
solution for automating entity extraction and linking because high quality,
structured data can:
The challenge is building a system that can adapt to real-world variations,
especially across semi-structured and unstructured documents without
sacrificing accuracy. Here is how we do it.
Scale Document AI relies on our
latest technology, Adaptive AI, to deploy refined machine learning models for
customers who demand high quality and low latency when it comes to document
processing. We leverage base models trained on millions of data points, and
further refine those models for each customer use case. This enables us to
extract and link entities from highly variable documents in seconds without
putting the burden of setup on the customer.
What’s unique about Adaptive AI is that we deliver a solution tailored to each
use case to extract the data our customers need at high quality — regardless
of any changes in document layouts. Unlike existing solutions, our machine
learning models thrive on challenging and varied documents by parsing the
structural layout of pages, contextualizing the meaning of words, and
understanding the relationships between different fields. We developed
Adaptive AI to actually understand the structure and the form fields’ meaning,
rather than simply learning where on a document to find a field (e.g.
understanding the vendor name instead of instructing that it is usually on top
left of document).
With Scale Document AI, you get:
Scale Document AI serves many industries across financial services,
insurance, real estate, logistics, manufacturing, energy, healthcare, and
government, across a variety of document types and use cases such as loan
origination, customer onboarding, invoice/receipt/bill processing, fraud
prevention, claims processing, title closing, shipment processing, and
clinical lab report extraction.
In logistics, we partnered with
Flexport, which is building the
platform for global trade, to significantly increase efficiency and reduce
costs in what used to be a manual effort for processing critical shipping
paperwork. We quickly deployed our Adaptive AI for important logistics
documents like Bill of Lading, Arrival Notices, and others to reduce data
extraction errors and improve compliance across Flexport’s global trade
network. James Chen, Flexport CTO, explained the impact of our partnership
at
Scale Transform, our conference earlier this year:
Another applicable area for Scale Document AI is financial services,
specifically bill pay services, loan origination, and claims processing.
Brex, a $7.4B startup modernizing
banking for businesses, uses Scale Document to power its new premium bill
pay product. When customers submit invoices in the Brex app or forward an
email with an invoice to the designated Brex email, our Adaptive AI extracts
all relevant information from these invoices instantly and accurately to pay
the bill, at higher quality and faster than off the shelf solutions.
We are excited to reimagine document processing to enable faster and better
workflows for challenging document types where conventional approaches don’t
hit the mark. If you want to achieve modern operational efficiencies through
AI and see tangible downstream improvements in business metrics, contact us
at documentai@scale.com or sign up on our