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INTERNET | Internet Software & Services / Billing, Expense Management and Procurement
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Founded Year

2012

Stage

Series C | Alive

Total Raised

$102.59M

Valuation

$0000 

Last Raised

$50M | 2 yrs ago

Mosaic Score

+60 points in the past 30 days

What is a Mosaic Score?
The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.

About AppZen

AppZen is an artificial intelligence powered SaaS tool for automating T&E expense report audit. The patented tool integrates with all existing expense reporting tools, such as Oracle, Concur, and NetSuite, to detect T&E fraud and compliance issues within minutes. AppZen uses Computer Vision and Natural Language Processing algorithms to capture and analyze expense report data, including document images, cross-check it with hundreds of data sources and social media, and notify the audit team in real-time of any compliance issues and fraud.

AppZen Headquarter Location

6201 America Center Drive Suite 300

Santa Clara, California, 95002,

United States

408-647-5253

Latest AppZen News

Why Autonomous AI is (finally) Disrupting Corporate Finance for Good

Jul 19, 2021

Why Autonomous AI is (finally) Disrupting Corporate Finance for Good In this special guest feature, Kunal Verma, CTO and Co-Founder of AppZen , discusses how technology like RPA and AI are having their breakout moments as company leaders realize they are no longer nice to have, but a business-critical tool to stay ahead of the competition. Kunal is responsible for the company’s product vision as well as overseeing the company’s R&D and data science teams. Kunal co-founded AppZen in 2012 when he developed its core artificial intelligence technology. Previously, he led research teams at Accenture Technology Labs that were responsible for developing AI-based tools for Fortune 500 companies. He earned his Ph.D. in Computer Science from the University of Georgia with a focus on semantic technologies. The need for accuracy, speed,and cost optimization has thrust automation into the spotlight as one of the most significant digital transformation drivers—especially given the events of the past year. When you look at the numbers , technology  like RPA and AI are having their breakout moments as company leaders realize they are no longer nice to have, but a business-critical tool to stay ahead of the competition. AI is helping organizations execute tasks that were previously hard or in some cases impossible to achieve efficiently, effectively, and accurately by leveraging valuable insights from copious amounts of structured and unstructured data. And it’s thanks to this ‘big data’ that democratizing data has become a reality—one where you remove any gatekeepers that create a bottleneck and limit access to important information. You no longer need to be a data scientist to access and understand what the data is telling you because the logic as to how you use the data is independent of the process of data generation. The advent of big data has really driven the rise of AI and where it is today, companies have to have good historical data to ingest into their AI platforms. The old adage is true – good data in – good results out. This approach enables cross-team functionality and ease of use when interacting with other parts of the business through things like data visualization and dashboards , which can be easily shared and understood by the C-suite all the way down. Despite several companies already leveraging automation, nowhere is AI currently having the biggest impact than on corporate finance departments, disrupting how finance teams operate and work —both within, and outside of, the organization. Finance teams have traditionally been plagued by manual processes, human oversight, as well as legacy technology. AI is changing all of that by removing barriers and making data much more accessible. Finance teams can now automate complex financial and compliance processes such as auditing documents—from expense reports and invoices, to packaging slips and receipts. Three AI technologies crucial to corporate finance In order to become a truly autonomous finance team, it’s vital to leverage three crucial AI technologies simultaneously —Computer Vision (CV), Natural Language Processing (NLP), and Semantic Analysis (sometimes called Semantic Understanding). This combination ensures the system can understand structured and unstructured data, while continuing to learn from billions of transactions, data points, and user feedback. Over the past few years, advancements in AI have enhanced Computer Vision technology to the extent where we can now easily read text from receipts—even if they’re barely legible like the ones you receive from yellow cabs. When auditing financial documents, deep learning based CV models are running behind the scene to extract information, while state of the art Natural Language Processing techniques from various research institutions help us understand the language. NLP is used in our everyday lives when we use virtual assistants like Siri and Alexa, but businesses are starting to explore applications to speed productivity. For example, natural language processing technology is being used to transcribe conversations in real time, which can then be used to extract data, allowing for AI to make decisions based on this information. With Semantic Analysis , you’re able to understand and build relationships between disparate, extracted data like dates, prices, discounts, payment terms, and line-level spend categories, removing the need for manual intervention to review otherwise unknown or unclassifiable pieces of data. For example, let’s say you receive an invoice from a colleague who took a client out to dinner a few nights ago—by leveraging semantic classification to draw inferences from the data, the system will be able to read and understand the receipt and that you ordered filet mignon, which is a type of meat, which is a type of food, but also that it is something that can be expenses according to company policy. Autonomous AI is driving true digital transformation There’s also a lot of emphasis being put on automation with technologies like Robotic Process Automation (RPA), which can easily handle repeatable tasks, manage structured data (only), and requires a good amount of human interaction. While RPA is a beneficial technology and works well with AI , corporate finance teams need something more that allows them to harness (both structured and unstructured) big data to become truly autonomous, which can only be done with AI. With accuracy requirements being pretty high in finance (e.g. compliance, audits, etc. ), AI adoption has been somewhat challenging, but autonomous AI (and the three core AI technologies) has been the ultimate disrupter. Being able to process invoices autonomously—from PDF to paper formats—allows approvals and decisions to be made without time-consuming manual human review that has historically taken weeks to accomplish. Modern Finance teams require autonomous AI-based solutions that do the heavy lifting and save time-consuming human review only for exceptions. Your team can instead focus attention on issues that require resolution, investigation, or nuanced decision making instead of sorting through mountains of expenses and invoices. They can also spend more time on what they do best: forecasting and supporting the company’s long-term, strategic financial goals and objectives. So, at the end of the day our journey to truly harnessing the power of AI is inextricably linked to big data and the ability to have a platform that can understand it to allow organizations to make valuable business decisions, driving efficiency, cost-savings and more. Sign up for the free insideBIGDATA  newsletter . Join us on Twitter: @InsideBigData1 – https://twitter.com/InsideBigData1

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Expert Collections containing AppZen

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

AppZen is included in 6 Expert Collections, including Regtech.

R

Regtech

1,342 items

Technology that addresses regulatory challenges and facilitates the delivery of compliance requirements in FIs. Regulatory technology helps FIs and regulators address challenges ranging from traditional compliance and risk management to data reporting and transmission.

A

AI in Fintech

155 items

S

SMB Fintech

1,073 items

A

AI 100 2019

100 items

A

Artificial Intelligence

7,340 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.

U

US-based SMB Fintech Companies

354 items

AppZen Patents

AppZen has filed 1 patent.

patents chart

Application Date

Grant Date

Title

Related Topics

Status

3/5/2014

10/4/2016

Educational psychology, Social networking services, Learning, Pedagogy, Educational technology

Grant

Application Date

3/5/2014

Grant Date

10/4/2016

Title

Related Topics

Educational psychology, Social networking services, Learning, Pedagogy, Educational technology

Status

Grant

AppZen Web Traffic

Rank
Page Views per User (PVPU)
Page Views per Million (PVPM)
Reach per Million (RPM)
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