Mojo is built on four pillars which when achieved, you have changed the game!
Copyright and Patented, 2018 PaperClip Inc.
The first pillar is security which is unique because it opens your processing to a global workforce requiring no infrastructure, no training, no supervisor and enhances cybersecurity at the same time. Mojo security removes the requirement to open back office solutions to third parties. Mojo when engaging the CrowdSource with confidential information shreds the content, therefore, Clipper (Crowd Source staff) never see context or the complete data element. Mojo results are also shredded and stored in the Shredded Data model. Today’s data is stored in an organized fashion whereby you can collect NPI or PHI associated with an individual. The Shredded Data approach has data fragments identified by a ciphered pointer (Snip-It ID) stored in two columns (e.g. 2 field record). Think about spending less on outsourced transcription services and removing all associated security threats.
The second pillar is accuracy which must be better or equal to my process today delivers. Mojo is a Microsoft Azure Cloud born PaaS service connected to Azure Cognitive Services (AI/ML) integrated with Crowd Sourcing providing roles necessary to perform quality control and machine training as needed. Deep Learning Convolutional Neural Networking (CNN) is the model most suited for Mojo handwriting recognition. Reaching a Six Sigma quality standard of 4 defects/million or 99.9% accuracy requires a process whereby defects can be quickly identified and resolved. This can also serve as a machine training event when new input is introduced and after several cycles, the machine then takes over.
The third pillar is speed (turnaround time) which must be faster than what you experience today. Mojo utilizes Azure service fabric platform providing on-demand scaling capabilities ensuring the input queues have the resources needed to make their SLA delivery time. Imagine a person that must enter data off a form containing 200 fields and takes 15 minutes; now imagine if you had 200 people entering data for just one field and it takes seconds. Turnaround time or speed not seen today are now possible with the advent of cloud computing.
The fourth pillar is economics which simply means, whatever process I’m addressing, it should cost less than what I do today. Reducing labor cost for many processes have created offshore business processing services. This usually means you must make an investment in items like brick and mortar, human resources, security, training and more. Mojo can eliminate all those concerns because content, when provided to the Crowd, is done in the PaperClip Patented Shredded Data model. Mojo is a growing collection of cloud-born applications designed to transform Big Data offering offshore economics without the offshore experience.
Mojo in Action
There are three primary uses of Mojo; transcription, translation and interpretive action on big data. The ability to approach big data with thousands of small special actions simultaneously creates turnaround times (TAT) never seen before. Processing thousands of forms, freeform pages, hours of audio and video within seconds is where big data begins.
Forms Processing Use Case
To receive a 10-page application with 50 fields to data to collect takes 30 seconds TAT. To receive a 100-page application with 500 fields to data to collect takes 30 seconds TAT.
Free-form Pages Use Case
To receive a 20-page handwritten manuscript written in Chinese to English text takes 30 seconds TAT. To receive a 200-page handwritten manuscript written in German to English text takes 30 seconds TAT.
Audio Use Case
To receive a 3-minute audio clip and process it to text takes 30 seconds TAT. To receive a 3-hour audio clip and process it to text takes 30 seconds TAT.
Interpretive Use Case
To receive thousands of pictures focused on real estate and ask questions of interior detail (i.e., the color of the paint in the living room, type of flooring in the kitchen) takes 30 seconds TAT.
Mojo is designed to process big data to a consistent TAT no matter its size. This is the magic of cloud computing and crowdsourcing.
Mojo Security
Mojo addresses security in two ways, content to Clippers and context in storage. In distributing thousands of SnipIts to thousands of Clippers, the key here is to remove all contexts to the SnipIt itself. A SnipIt may present the image of “John“ to a Clipper, the Clipper has no knowledge of the source. The SnipIt could be from a job application, parking ticket, retail order form, insurance application, and other sources. Second is to take sensitive fields (i.e. SSN, Policy Number, Driver License, etc.) and slice them into smaller SnipIt whereby the entire value is never presented. Let take SSN as our example, factored in half, one Clipper will see an image of “12345” while the second Clipper will see an image of “56789”. To the Clipper, these are just numbers, possible address, phone number, account, birth date or others.
Mojo stores the data just as it was distributed, no contexts. SnipIts once processed are stored in an optimum scheme reference only by its ciphered key. This Shredded Data Storage (SDS) model provides perfect secrecy whereby if obtained by nefarious means, the data would be useless. Taking a database by itself would have no value. Criminals themselves would have to process the data out and that Mojo can watch for and stop. The days of copying data out without any notice are over; Mojo’s SDS now makes its data “Shredded at Rest”.
