ReposiTrak Adds Artificial Intelligence to Compliance Management System

An Artificial Intelligence engine then finds the relevant information and performs a verification check. Proprietary algorithms finally adjudicate whether …

MURRAY, Utah–(BUSINESS WIRE)–ReposiTrak, Inc., the industry leader in compliance, food safety and risk management for the retail supply chain, has enhanced its Optical Character Recognition (OCR) capabilities and added Artificial Intelligence (AI) to its compliance management system for improved automated document review accuracy. These new features enable a higher level of automation that will deliver even more time savings in reviewing and accepting documents for compliance.

As a result of the new functionality, suppliers can readily submit image-based documents and picture files such as jpegs directly for uploading into ReposiTrak’s cloud-based compliance management system. The OCR engine in ReposiTrak converts a document image into text and then scans the text to determine whether it’s an acceptable form. An Artificial Intelligence engine then finds the relevant information and performs a verification check. Proprietary algorithms finally adjudicate whether the document meets the user’s compliance requirements.

“With this added capability, we have solid confidence the data from any document entered into the system more accurately reflects the intended purpose, preventing mistakes, oversights or intentional uploads of non-compliant documents,” explained Jozef Jamrich, CTO of ReposiTrak.

Collection of compliance documents has grown as ReposiTrak’s compliance management network has more than 85,000 points of connections between retailers, wholesalers and suppliers. Customers have specific requirements for each of their suppliers and the number compounds to thousands of hours spent manually reviewing documents.

“These new features demonstrate our continued commitment to being the leader in technology for automated compliance systems,” said ReposiTrak CEO Randy Fields. “It will save companies even more time in collecting documents from their suppliers and at the same time make it easier to ensure they’re getting the right documents.”

The ReposiTrak Speed Retail Platform drives growth and supports all supply and demand chain activities for retailers, manufacturers, and their trading partners, consisting of three product families; Compliance & Risk Management, Supply Chain Solutions, and MarketPlace Sourcing and B2B Commerce. Delivered via one technology platform, all the applications are mutually reinforcing and work synergistically to create value and positive impact across the entire enterprise.

About Park City Group and ReposiTrak®

Park City Group (NASDAQ: PCYG) is a Software-as-a-Service (“SaaS”) provider that brings visibility to the consumer goods supply chain through its ReposiTrak, Inc. subsidiary. ReposiTrak is The Speed Retail Platform, with three product families; Compliance & Risk Management, Supply Chain Solutions, and MarketPlace Sourcing and B2B Commerce. The platform provides retailers and suppliers with a robust solution suite to help enhance operational control and increase sales, while enabling them to protect their brands, reduce risk and remain in compliance with regulatory requirements. More information is available at and at

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Commentary: Three observations about the adoption of distributed ledger technology in supply chain

On August 4, the University College of London’s Center for Blockchain Technologies (UBL CBT) published Distributed Ledger Technology in the …

FreightWavesfeatures Market Voices – a forum for voices with unique knowledge of numeroustransportation/logistics/supply chain sectors, as well as other criticalexpertise.

On August 4, the University College ofLondon’s Center for Blockchain Technologies (UBL CBT) published Distributed Ledger Technology in the Supply Chain,“a market report looking at the adoption of Distributed Ledger Technology(DLT) in physical supply chains.” The CBT added that the report “is the firstcomprehensive outlook on the state of DLT in the global physical supply chainsector.”

In this article, I synthesize threethemes that the authors of this report identify as affecting the broad adoptionof distributed ledger technology in global supply chain networks.

The report assessed 105 DLT projects.

Track and trace is the most common use-case across industries

The globalization of supply chains presents an advantage – goods can be sourced at lowest cost from any part of the world. However, that advantage comes with an attendant disadvantage – individual consumers, business customers and regulators all require information about products that have been sourced from far-flung parts of the world.

Track & Trace DLT Projects | Source: DLT in the Supply Chain

Given the size of the global food retail market, the complexity of food supply chains around the world, and the need to monitor and minimize outbreaks of food-borne illnesses, it is not surprising that retail food supply chains account for the majority of track and trace DLT in supply chain projects.

Projects by Sector and Focus | Source: DLT in the Supply Chain

The report highlights IBM Food TrustTM,an ecosystem of food industry participants who share information with oneanother to create a more transparent and secure global food supply chain. Thisproject already counts some of the world’s biggest food companies as members.

Onepromising early application of DLT is the digitization of manual, paper-basedprocesses in supply chain logistics

Onearea in which we may see rapid adoption of DLT is in the digitization ofmanual, paper-based processes and record-keeping related to supply chainlogistics. This is particularly relevant for the record-keeping required by theregulatory bodies involved in the import and export of goods around the world.Some port authorities are experimenting with blockchain-based bills of lading.One of the startup projects that the report highlights is CargoX, whose chiefoperating officer was a presenter at The New York Supply Chain Meetup’sone-year anniversary event in November 2018. Projects like CargoX haveapplication across several industries.

Onthe other hand, as the authors state, “However, since supply chains typicallyinvolve many and varied participants it is also among the most complex usecases to implement. As with all blockchain deployments, benefits are only realizedat scale once critical mass is obtained. Consequently, whilst a raft of proofof concepts have been completed over the past three years, rollout at scale isstill a work in progress. This is challenging because it requires a collectiveapproach with industry-level engagement.”

I have written that the cultural obstacles toDLT and blockchain adoption in supply chain logistics may be more difficult toovercome than the technical difficulties. This is because private, permissionedimplementations of DLT in supply chain need to be interoperable with oneanother. This requires intra- and inter-industry collaboration. It requirescollaboration between once sworn competitors. It requires collaboration betweenstartups and established companies.

DLTin financial applications may take longer to gain widespread adoption than onewould expect

In my opinion, applications of DLT insupply chain finance or trade finance are possibly the most exciting and mostsignificant in terms of their potential economic impact. However, I believethey may be the last to gain broad adoption amongst enterprises. Applicationsin supply chain management and supply chain logistics will need to become moremature and widespread before applications in supply chain finance gain wideradoption. The authors of this report explain why this may be the case.

Applications in this area include: payments enabled by smart contracts; selling directly to individual consumers; and alternative methods of obtaining and deploying working capital. The chart below shows how the projects studied for this report are distributed.

Financial Transactions Projects by Sector | Source: DLT in the Supply Chain

The authors point out two reasons financial transactionapplications of DLT in supply chain could take longer to gain adoption than theothers. First, distributed ledger technologies and cryptocurrencies are stillpoorly understood. The lack of understanding of the technology creates negativeperceptions. This creates barriers to adoption in financial transactions.Second, financial transactions must adhere to a high degree of regulation andlegal scrutiny. It takes time for a regulatory framework that accommodates newpayment methods to be developed. As I wrote above, supply chain financeapplications of DLT will become more prevalent once supply chain management andsupply chain logistics applications become more prevalent.

Conclusion: DLT in supply chain is here to stay, even ifit takes time

The authors conclude by stating that DLT is set to transform physicalsupply chains, even though there is still much work to be done beforedecentralized systems become a reality for real-world applications at scale.They end the report with three observations. First, data quality remains aconcern in DLT in supply chain applications. Second, input and outputconnections between DLT supply chain applications and physical supply chainsmust be built and defined. Lastly, “the new co-opetition model of consortia isnot an easy one to implement. It requires a new way of working for companiesand also is potentially challenging from a regulation and antitrustperspective. New collaborative forums can play an important role here to bringstakeholders together and drive industry level adoption.”

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Why Big Data in Procurement is Crucial for Businesses in 2019? | SpendEdge’s Latest Article

Big data analytics allows businesses to examine large and varied data sets obtained from different online channels. It traces products across the entire …


SpendEdge, a leading provider of procurement market intelligence solutions, has announced the completion of their latest article on the benefits of big data in procurement.

This press release features multimedia. View the full release here:

According to SpendEdge’s new study, big data will soon change the way businesses devise strategies to become market leaders. It possesses the potential to consolidate relevant information from multiple streams onto single dashboards and help procurement professionals make informed decisions. Businesses will also witness changes in the way applications are developed and improve procurement functions by better understanding supply chain needs in real-time.

Wondering how you can understand supply chain needs in real-time? Request a free proposal to leverage our portfolio of customized procurement solutions.

At SpendEdge, we understand the importance of big data in procurement. Therefore, we have highlighted some key benefits of big data in procurement that companies should aim to reap to improve their productivity.

Key Benefits of Big Data in Procurement

Improves supply chain traceability

Big data analytics allows businesses to examine large and varied data sets obtained from different online channels. It traces products across the entire supply chain and creates opportunities for businesses to boost procurement productivity and reduce costs. Big data in procurement also helps CPOs to take forward-looking viewpoint based on accurate information.

Inability to trace supply chain can hamper the productivity of businesses. Contact our experts to know how you can boost supply chain efficiency.

Informed sourcing and procurement decisions

Analyzing and systematically extracting information from large data sets is a tumultuous task. With big data analytics, companies can easily gain more contextual information by transforming unstructured data available in different forms into accurate datasets. They can also perform a comprehensive spend analysis and improve their sourcing process.

Making informed sourcing and procurement decisions require accurate datasets. Request a free demo from our experts to access our smart procurement solutions.

Improves supplier relationships and new business models

Big data analytics possess the potential to change volume based purchasing programs to value based programs. Suppliers who can add more value to the organization will be preferred. This will lead to mutation in business models and supplier relationships.

To know how you can implement new business models and improve transparency in supplier relationships, request more information from our experts now!

About SpendEdge:

SpendEdge shares your passion for driving sourcing and procurement excellence. We are the preferred procurement market intelligence partner for 120+ Fortune 500 firms and other leading companies across numerous industries. Our strength lies in delivering robust, real-time procurement market intelligence reports and solutions.

Want more information? We’re happy to help! Tell us more about your business challenges.

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IBM To Bring 4000 Suppliers Onto New Blockchain Platform

TYS will likely compete with projects like VeChain, WaltonChain, R3 and others that seek to revolutionize supply chain with distributed ledger …

Today, IBM and Chainyard announced Trust Your Supplier (TYS), a blockchain-based platform for simplifying supply chain management and supplier verification and onboarding. Within the coming months, IBM plans to bring 4,000 of its North American suppliers onto the new network, potentially gaining an edge in the world of supply chain management.

TYS already has a formidable list of participants, including major companies such as Anheuser-Busch InBev, Cisco, GlaxoSmithKline, Lenovo, Nokia, Schneider Electric and Vodafone. The platform is meant to revolutionize the traditional methods of supplier management. Currently, these processes largely lack automation, which has proven to be cumbersome for managing the finer aspects of tracking shipment documents, ISO certifications, bank account information and other ancillary documentation.

The new blockchain solution is expected to create an immutable audit trail on the blockchain and reduce inefficiencies related to the industry. The company hopes to significantly reduce the risk of fraud and errors and bring IBM to the forefront of the supply chain DLT, which is expected to support more than $2 trillion of goods and services by 2023, according to Gartner Inc.

SIMETRI ResearchSIMETRI Research

Trust Your Supplier works by creating a digital passport that allows suppliers to share information with any permissioned buyer on the network. Third-party validators, such as Dun & Bradstreet, Ecovadis and RapidRatings provide outside verification or audit capabilities directly on the network.

It’s the latest move from a tech giant seeking to establish itself as an industry leader in enterprise blockchains. In 2016 the company created the cloud-based IBM Blockchain Platform to allow enterprise clients quickly develop their own networks. It also supported and partnered with blockchain companies involved in industries as diverse as food, international payments, credit, and shipping.

TYS will likely compete with projects like VeChain, WaltonChain, R3 and others that seek to revolutionize supply chain with distributed ledger technology. While these projects have been in the space for much longer, they have also remained fairly limited in terms of adoption. Big Blue is staking its territory, and the competition will need to react.

The Trust Your Supplier network is currently in limited availability, with a commercial launch planned later in Q3 2019. IBM itself currently has over 18,500 suppliers around the world, and expects to onboard 4000 of them in the next few months. IBM Procurement projects a 70 to 80 percent reduction in the cycle time to onboard new suppliers, with a potential 50 percent reduction in administrative costs within its own business.

While streamlining supply chains is likely to have knock-on effects for consumers, it’s clear that the main purpose of the new platform isn’t just to let you know where your groceries are from. It’s also hitting at what businesses care about most – cost savings.

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Global Artificial Intelligence in Supply Chain Market Growth Overview of Influencing Players Like …

In this Artificial Intelligence in Supply Chain report, a market study and overview is carried out by considering market drivers, market restraints, …

In this Artificial Intelligence in Supply Chain report, a market study and overview is carried out by considering market drivers, market restraints, opportunities and challenges for a particular business. This report acts as a perfect window to the ICT industry which explains what market definition, classifications, applications, engagements and market trends are. Leading Players of Global Artificial Intelligence in Supply Chain Market are NVIDIA, IBM, Intel Corporation, Xilinx, Samsung Electronics, Samsung Electronics America, Micron Technology, Microsoft, Amazon, SAP, Oracle, Logility, LLamasoft, Inc., ClearMetal, Splice Machine, Cainiao Networks, FedEx, DHL, H. Robinson, E2open, RELEX Solutions, Teknowlogi, Presenso, Fraight AI, FedEx Supply Chain, Deutsche Post, Alibaba Group, SoftBank Group, Baidu, Inc., Salesforce, Interactions LLC, Lexalytics, Inc., FedEx Express Canada, Next IT, RetailNext, Sentient Technologies, ViSenze – AI for Visual Commerce, Amazon Web Services and others.

This Artificial Intelligence in Supply Chain market research report intensely analyses the potential of the market with respect to current scenario and the future prospects by considering several industry aspects of ICT industry. The report also recognizes and analyses the rising trends along with major drivers, challenges and opportunities in the market. This report provides major statistics on the market status of global and regional manufacturers and is a helpful source of assistance and direction for companies and individuals interested in the ICT industry. The company profiles of all the chief and dominating market players and brands who are taking steps such as product launches, joint ventures, mergers and acquisitions are mentioned in the report.

The Global Artificial Intelligence in Supply Chain Market is expected to reach USD 10,787.2 million by 2025 from USD 21.21 million in 2017 and is projected to grow at a CAGR of 8.1% in the forecast period of 2018 to 2025.

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Recent Industry Developments

The artificial intelligence in supply chain is a field holds secure development prospects, inferable from which, the key players are concentrating on building up an incorporated arrangement including equipment and programming. Moreover, to grow their client achieve, a few merchants have teamed up with wholesalers and end clients for item appropriation. The expanding conspicuousness of parallel preparing applications is prompting expanded selection of the innovation in logical teaches, for example, counterfeit consciousness and information science. Associations are using counterfeit measures to extricate significant insights of information for giving creative items and enhancing client encounter; in this manner, expanding income openings.

The global artificial intelligence in supply chain market is fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market in order to sustain in long run. The report includes market shares of artificial intelligence in supply chain market for global, Europe, North America, Asia Pacific and South America.

In 2016 artificial intelligence and machine learning emerging as the next big technology has seen a race for artificial intelligence, with a number of acquisitions and large technology vendors such as IBM, Google and Amazon are launching a new artificial intelligence-enabled product.

In 2017, Teknowlogi Launches a first cloud-based solution built on artificial intelligence for the logistics industry. It is a next-generation platform category, representing a much-needed advancement for traditional industry logistics system.

Artificial Intelligence (AI) in supply chain is a creation of wise and smart machines that work, respond and react like people. It is utilized to enhance the proficiency of day by day undertakings. Advancing innovation, selection of robots and drones, driverless tractors, crop health checking, and automated water system framework are a part of the applications that credited to the high development of the global artificial intelligence in supply chain AIS showcase. Highly proficient yield examination is offered by drones and software programming advancements, for example, radars and GPS framework, empower to reduce weight on existing stressed workforce. In addition, remote detecting systems are also used to view the quality and yield creating capacity of a farming area.

Key Highlights of the Artificial Intelligence in Supply Chain Market Report:

Get enlightened information available on the Artificial Intelligence in Supply Chain market worldwide.

Identify growth in various segments and investment opportunities. Benchmark fulfillment adjacent the key adversary.

The main criterion related to Artificial Intelligence in Supply Chain industry area including the overall structure of the product, numbers of applications, price, demand, and supply are enfolded in this report.

The research of emerging Artificial Intelligence in Supply Chain market section and extant industry segments will aid the investors or novice in formulating and developing business strategies.

Facilitates decision making in view of noteworthy and gauging information also the drivers and limitations available of the market

Global Artificial Intelligence in Supply Chain Market share assessments for the regional and country level segments.

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Market Segmentation

Based on application

  • Fleet management,
  • Supply chain planning,
  • Warehouse management,
  • Virtual assistant,
  • Risk management,
  • Freight brokerage and others

Based on offering

  • Hardware,
  • Software and
  • Services

By Geography

  • Asia Pacific (China, South Korea, Japan, India, Australia, Singapore, Thailand, Indonesia, Malaysia, Philippines, Rest of Asia-Pacific).
  • North America (US, Canada, Mexico).
  • Europe (Russia, Turkey, Belgium, Netherlands, Switzerland, Spain, France, Germany, Italy, UK, Rest of Europe.
  • South America (Brazil, Argentina, Rest of South America).
  • Middle East and Africa (South Africa, Egypt, Saudi Arabia, United Arab Emirates, Israel, Rest of Middle East and Africa).

Based on technology

  • Machine learning,
  • Natural language processing (NLP),
  • Context-aware computing and
  • Computer vision

Based on industry

  • Automotive,
  • Aerospace,
  • Manufacturing,
  • Retail,
  • Healthcare,
  • Consumer-packaged goods,
  • Food & beverages and others

Market Drivers and Restraints:

  • Growth of big data
  • Demand for greater visibility and transparency in supply chain data and processes
  • Adoption of AI to improve consumer services and satisfaction.
  • High Information and data storage capacity
  • High computing power and parallel processing capabilities
  • Lack of people power
  • Data inefficiency in building proper AI algorithms.

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Major Highlights of TOC:

Chapter One: Artificial Intelligence in Supply Chain Market Industry Overview

1.1 Artificial Intelligence in Supply Chain Industry

1.1.1 Overview

1.1.2 Products of Major Companies

1.2 Artificial Intelligence in Supply Chain Market Segment

1.2.1 Industry Chain

1.2.2 Consumer Distribution

1.3 Price & Cost Overview

Chapter Two: Artificial Intelligence in Supply Chain Market Demand

2.1 Segment Overview



2.1.3 Other

2.2 Artificial Intelligence in Supply Chain Market Size by Demand

2.3 Artificial Intelligence in Supply Chain Market Forecast by Demand

Chapter Three: Artificial Intelligence in Supply Chain Market by Type

3.1 By Type

3.1.1 TYPE 1

3.1.2 TYPE 2

3.2 Artificial Intelligence in Supply Chain Market Size by Type

3.3 Artificial Intelligence in Supply Chain Market Forecast by Type

Chapter Four: Major Region of Artificial Intelligence in Supply Chain Market

4.1 Artificial Intelligence in Supply Chain Sales

4.2 Artificial Intelligence in Supply Chain Revenue & market share

Chapter Five: Major Companies List

Chapter Six: Conclusion


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