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OrNsoft Expands CEErtia Sales Network to APAC Region

OrNsoft Corporation expands workforce to accommodate increased demand for latest document management software, CEErtia. CEErtia is an AI-powered document & data management software currently in use by major European corporations.

This week, OrNsoft Corporation, a Miami-based international software development company has announced that they are expanding their sales network to allow for partnerships in the APAC region. This announcement comes after increased demand overseas for their newest software product, CEErtia, an AI-powered document management solution that is currently being used to aid document-handling processes and compliance in a variety of industries, from finance, to legal, to energy. CEErtia was created last year and has quickly garnered attention from large corporations in France and has begun to draw interest from several business sectors for its powerful data management and document classification and verification features. "We're elated to see that the interest for our newest solution has been consistently growing for the past year, and we're ready to supply our sales operation overseas with the necessary manpower and resources", said OrNsoft founder and CEO Johnny Saffar. Since 2010, OrNsoft has steadily grown in the European market. "The expectation is that this expansion from our European operation into Asia and Middle East will position us as a major player for custom AI software solutions in the APAC region," added Saffar.

About OrNsoft Corporation

Founded in 2009 in Miami, FL, OrNsoft specializes in custom turnkey AI software for process optimizations. OrNsoft prides itself on their willingness to adapt to unique requests from their corporate clients. By 2011, OrNsoft had already serviced more than 2,000 customers worldwide and gained recognition from some of the largest IT companies in the industry, including Microsoft, Google, Oracle, Adobe and Apple. Their reputation and expertise have allowed them to work as a vendor with prominent organizations and corporations, including various government agencies worldwide.

16 Apr / in Enterprise, General, Press Release

Document Management and Data Extraction in Business

Document management and data extraction encompass the processes that collect and organize data. Ideally businesses want to do this in a way that allows them to best analyze the data and make educated decisions on the direction of their business. Documents contain data. It is well-known that every business relies on data to make decisions about their future.

Document Management, Data Extraction, and Verification

Stemming from document management are the processes of data extraction, verification, and classification. These processes take up a lot of time and resources in every business due to the archaic methods through which they are achieved. That's where artificial intelligence can step in to improve accuracy & efficiency. Data extraction is the process of collecting disparate types of data from different sources. This process makes it possible to merge, measure, and refine information so that it may be put away into a centralized storage space to be stored and rearranged for analysis. These locations may be cloud-based, on-site, or hybrids of both. Document classification is the process of sorting and labeling documents by category depending on their content and context. Data and document verification is where the authenticity of data and documents are verified. The legitimacy of individual information like name, age, and address is reviewed. In the early days of document management and data extraction, the processes relied almost entirely on human input. Relying solely on humans left their results riddled with miscalculations stemming from human errors and confusion. "Data analysis" back then was mainly providing monthly reports and looking backward, not much creation of business projections. These processes can costs companies millions of dollars in labor every year because they need to be done, and up until now they could only pay people to perform these tasks manually. Artificial intelligence allows these processes to become automated, allowing humans to focus on higher-level analysis and to worry less about human error.

________

Inaccurate data can cost businesses productivity loss and missed opportunities on a regular basis. Documents and data need to be stored and organized in a way that allows analysts to easily sort and search. Optical character recognition, aka OCR, has been a popular technology to aid with document management and data extraction. Recently, artificial intelligence has pushed OCR to new heights - Businesses are benefiting substantially from this technology. The convenience they are gaining by moving to digital document management is facilitating growth, organization, and accuracy across the board.

15 Apr / in Technologies

Supervised Learning vs. Unsupervised Learning

Supervised and unsupervised learning are the processes that allow artificial intelligence to emulate the human behavior of studying data. As we covered in our last article, artificial intelligence involves both machine learning and deep learning. Now you may wonder, “How exactly do these machines analyze data to learn from these processes?”

Supervised Learning

Supervised learning, as the name suggests, works with the presence of a human supervisor providing feedback through the analysis process. The algorithm requires guidance and has “labels” associated with the data to give accurate results. Normally, it is given input and output variables to get the answer. Supervised learning works best when it knows what to look for, it’s a simpler method that works best with smaller data. Supervised learning is categorized in two ways. One categorization, regression, is used to predict numerical values. This is also where the output variable is a real value (like future revenue or cash flow). Classification, the other categorization, estimates categorical values and can predict several conclusions.

Unsupervised Learning

Unsupervised learning, unlike its counterpart, does not need to be monitored by a human. Its speciality is to discover all sorts of unknown data, working on its own to discover information. There are two ways unsupervised learning treats data: clustering, which processes data and divides it into groups; and association, which discovers the relationships between variables in large databases.

________ The factors of your data that should be considered when choosing your model for data analysis should be structure and volume. Supervised learning will be your best bet if you are sure of the outcome. If you are unsure and want to develop some insights from a big data set, you should choose to use unsupervised learning. However, remember that unsupervised learning is not 100% accurate at first, but does get better with time.

13 Apr / in Technologies

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OrNsoft Expands CEErtia Sales Network to APAC Region

OrNsoft Corporation expands workforce to accommodate increased demand for latest document management software, CEErtia. CEErtia is an AI-powered document & data management software currently in use by major European corporations.

About OrNsoft Corporation

Document Management and Data Extraction in Business

Document Management, Data Extraction, and Verification

________

Supervised Learning vs. Unsupervised Learning

Supervised Learning

Unsupervised Learning

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Related

Latest News

OrNsoft Expands CEErtia Sales Network to APAC Region

OrNsoft Corporation expands workforce to accommodate increased demand for latest document management software, CEErtia. CEErtia is an AI-powered document & data management software currently in use by major European corporations.

About OrNsoft Corporation

Share:

Document Management and Data Extraction in Business

Document Management, Data Extraction, and Verification

________

Share:

Supervised Learning vs. Unsupervised Learning

Supervised Learning

Unsupervised Learning

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