AI Analysis X Ray

AI Analysis X Ray — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

MyRadar

MyRadar is a free weather forecasting application developed by Andy Green and his Orlando, Florida-based company ACME AtronOmatic (ACME). The app began operations in 2008 and ran on government-provided weather and radar data for its first decade. In 2019, ACME launched personal satellites to improve predictions of ongoing weather. The app received funding to improve its radar and imaging from the Federal Communications Commission (FCC), National Oceanic and Atmospheric Administration (NOAA), and the Office of Naval Research (ONR). ACME created a weather data satellite constellation named "Hyperspectral Orbital Remote Imaging Spectrometer" (HORIS), which utilizes machine learning and artificial intelligence (AI) to create a current weather map. With the introduction of additional features, including the detection of wildfires and illegal fishing, the app has more broadly become an environmental intelligence app since 2022. In 2024, the app partnered with the Total Traffic and Weather Network (TTWN) to provide traffic flow and incident data for users with paying subscriptions via CarPlay and Android Auto. == History == The app's creator, Andy Green, had created internet tech since the 1980s. His first major project was the development of a public access internet service company based in Rhode Island, which he later sold to finance the creation of ACME AtronOmatic ("ACME" for short), based in Orlando, Florida. The first major app created by ACME was called "Flightwise", which provided users with flight tracking information. In summer 2008, Green had the idea to use the animated location tracker already built-in to Flightwise to make a stand-alone weather forecasting app after wondering if a meal he was eating outdoors would get rained out. MyRadar was launched in 2012 out of an office in Orlando. Despite running solely off of free government-provided weather and radar data for the first decade after launch, Green said the app "took off like wildfire" in downloads. In December 2017, the app partnered with "TripIt" to provide users with information about flight delays and gate changes, eliminating the need for a separate app like Flightwise. In 2019, ACME launched their first personal satellite for the app, a small prototype from New Zealand, as part of an effort to provide detailed imagery and improved predictions of ongoing weather unique to the app. More satellites were eventually launched by ACME to create a weather data satellite constellation named "Hyperspectral Orbital Remote Imaging Spectrometer" (HORIS), monitored by ground stations maintained by Kongsberg Satellite Services. HORIS operates MyRadar by taking the environmental data and imagery it collects and pairing it with machine learning and artificial intelligence (AI) to create a real-time weather map. In 2022, HORIS was expanded upon after ACME won approval from the Federal Communications Commission (FCC) to improve their satellite constellation to include 250 satellites or more. The main batch of satellites were PocketQubes, which entered the atmosphere on May 2, 2022, by Rocket Lab Electron launched from New Zealand, with the additional purpose to test and validate the existing satellites in orbit. In October 2022, ACME received a US$150,000 Small Business Innovation Research (SBIR) grant from the National Oceanic and Atmospheric Administration (NOAA) to improve the app's wildfire detection and air quality measurement technology to better detect smoke, aerosols, fire hotspots using satellites and aerial drones. On August 18, 2023, phase two of the NOAA grant was approved, providing an additional US$650,000 to aid in the app's aforementioned goals by launching a pair of CubeSat satellites to provide high-definition infrared imagery. On September 8, 2023, ACME secured another US$1,200,000 in crowd funding to aid accomplishing the goals of the NOAA grant by expanding the app's workforce from 35 to 100 employees by the end of 2024. In January 2024, MyRadar partnered with Total Traffic and Weather Network (TTWN) to provide traffic data overlaid with its pre-existing weather graphics for users in the United States. The partnership allowed for the app to additionally become a tool for navigation. This officially became a feature days later on January 8, 2024, when the app was made compatible with Apple's CarPlay. On February 7, 2024, the Android equivalent Android Auto also gained the ability to display the app on car interfaces. In March 2024, the app launched a "meteorological wedding planning service" in the United States and Canada for prices between US$1,000 and US$5,000, in which users can request a personal meteorologist to provide an in-person meeting about the best dates for a wedding, and on-call local weather updates the day of. Scheduled for February 2025, four more satellites to help with the NOAA-sponsored wildfire detection are to be launched, and the first by ACME to have AI processing in the satellites themself and not computers on the ground, allowing for quicker transfer of information. == Features and general information == The app's primary function is to provide weather forecasting and prediction to users. The app includes toggleable options to track and send alerts to users for rain, wind patterns, earthquakes, tornadoes, tropical cyclones, wildfires, and more. In early 2020, a feature was added to track orbital objects such as the International Space Station. In May 2022, with the imagery improvement of HORIS, the app gained the secondary abilities to better monitor algae blooms, coral reefs, illegal fishing, and wildfires. In January and February 2024, the ability to display traffic flow and incident data in a feature called "RouteCast" was added, and can be displayed in video and 3D options via CarPlay and Android Auto for users with paying subscriptions. The app also provides annual tropical storm and tornado outlooks for their respective seasons, gathered through satellite and aerial drone data, as well as through on the ground storm chasers.
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Carrier cloud

In cloud computing, a carrier cloud is a class of cloud that integrates wide area networks (WAN) and other attributes of communications service providers’ carrier-grade networks to enable the deployment of highly-complex applications in the cloud. In contrast, classic cloud computing focuses on the data center and does not address the network connecting data centers and cloud users. This may result in unpredictable response times and security issues when business-critical data are transferred over the Internet. == History == The advent of virtualization technology, cost-effective computing hardware, and ubiquitous Internet connectivity have enabled the first wave of cloud services starting in the early years of the 21st century. But many businesses and other organizations hesitated to move to more demanding applications, from on-premises dedicated hardware to private or public clouds. As a response, communications service providers started in the 2010/2011 time frame to develop carrier clouds that address perceived weaknesses in existing cloud services. Cited weaknesses vary but often include possible downtime, security issues, high cost of custom software and data transfer, inflexibility of some cloud apps, poor customer and nonfulfillment of service level agreements (SLAs). == Characteristics == To enable the deployment of time-sensitive and business critical applications in the cloud, the carrier cloud is designed to match or even exceed the characteristics of on-premises deployments. Therefore, the carrier cloud is characterized by some or all of the following items: Configurable, elastic network performance: Typical cloud computing solutions use the best effort of the public Internet to connect cloud users and data centers. This approach provides instant connectivity but does not offer control over network capacities, latencies, and jitter. Carrier clouds address these gaps with content delivery networks and/or dedicated virtual private networks (VPN) at OSI layers 1 (optical wavelengths), 2 (data link layer), and 3 (network layer). These VPNs can be configured to offer the desired performance parameters and exhibit the same type of elasticity for the network that regular clouds provide for servers and storage. To achieve the requested performance parameters, such as low latency, cloud applications can be (automatically) allocated to distributed data centers that are close enough to the cloud users. Automatic resource placement: For a cloud with multiple data centers, information about both the data center and the connecting network is relevant for a decision of where to place cloud images and storage volumes. For this decision, carrier clouds can obtain relevant information about the network, e.g., using the Application-Layer Traffic Optimization (ALTO) protocol. High level of security and governance: Cloud application providers are subject to general and domain specific security, privacy, and governance requirements and regulations, such as the European Data Protection Directive and the U.S. Health Insurance Portability and Accountability Act. For added security, the wide area network of the carrier cloud can provide segregated encrypted or unencrypted network links that are not accessible from the general Internet. At the data center, the carrier cloud provides e.g. virtual private servers, management processes, logs, and documentation to fulfill security and governance rules. Location control: Fundamentally, cloud users should not be concerned with the geographic location of their cloud resources. However, privacy and other regulations may mandate that certain types of data must not be sent outside a national jurisdiction or other geographical region. Open APIs: Carrier clouds provide graphical user interfaces and Web application programming interfaces that allow cloud application providers to set up, manage, and monitor both, the data center and the WAN, of their cloud services. == Architecture == Carrier clouds encompass data centers at different network tiers and wide area networks that connect multiple data centers to each other as well as to the cloud users. Links between data centers are used for failover, overflow, backup, and geographic diversity. Carrier clouds can be set up as public, private, or hybrid clouds. The carrier cloud federates these cloud entities by using a single management system to orchestrate, manage, and monitor data center and network resources as a single system.
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Content as a service

Content as a service (CaaS) or managed content as a service (MCaaS) is a service-oriented model, where the service provider delivers the content on demand to the service consumer via web services that are licensed under subscription. The content is hosted by the service provider centrally in the cloud and offered to a number of consumers that need the content delivered into any applications or system, hence content can be demanded by the consumers as and when required. Content as a Service is a way to provide raw content (in other words, without the need for a specific human compatible representation, such as HTML) in a way that other systems can make use of it. Content as a Service is not meant for direct human consumption, but rather for other platforms to consume and make use of the content according to their particular needs. This happens usually on the cloud, with a centralized platform which can be globally accessible and provides a standard format for your content. With Content as a Service, you centralize your content into a single repository, where you can manage it, categorize it, make it available to others, search for it, or do whatever you wish with it. == Overview == The content delivered typically could be one or more of the following The technical terminology related to equipment or spares that is required to procure or design the materials The industrial terminology of the equipment or spares Technical values pertaining to various types, specifications, applications, characteristics of equipment or spares Sourcing information which will help in procurement or supply-chain management of equipment or spares Descriptive specifications of equipment or spares based on the product reference number or identifier UNSPSC codes or industry practiced classifications ISO, IEC compliant terminology Ontology or Technical Dictionary of products & services Predefined content for specific business needs The term "Content as a service" (CaaS) is considered to be part of the nomenclature of cloud computing service models & Service-oriented architecture along with Software as a service (SaaS), Infrastructure as a service (IaaS), and Platform as a service (PaaS).
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Distributed Common Ground System

The Distributed Common Ground System (DCGS) is a system which produces military intelligence for multiple branches of the American military. == DCGS Programs == DCGS-N - DCGS for the United States Navy DCGS-A - DCGS for the United States Army AF DCGS - DCGS for the United States Air Force DCGS-MC - DCGS for the United States Marine Corps DCGS-SOF - DCGS for the United States Special Operations Forces IS&A Support Center - DCGS-A Help Desk for the United States Army - https://dcgsahelp.max.gov/ - Max.gov sunset 15 December 2023 == Description == While in U.S. Air Force use, the system produces intelligence collected by the U-2 Dragonlady, RQ-4 Global Hawk, MQ-9 Reaper and MQ-1 Predator. The previous system of similar use was the Deployable Ground Station (DGS), which was first deployed in July 1994. Subsequent version of DGS were developed from 1995 through 2009. Although officially designated a "weapons system", it consists of computer hardware and software connected together in a computer network, devoted to processing and dissemination of information such as images. The 480th Intelligence, Surveillance and Reconnaissance Wing of the Air Combat Command operates and maintains the USAF system. A plan envisioned in 1998 was to develop interoperable systems for the Army and Navy, in addition to the Air Force. By 2006, version 10.6 was deployed by the Air Force, and a version known as DCGS-A was developed for the Army. After a 2010 report by General Michael T. Flynn, the program was intended to use cloud computing and be as easy to use as an iPad, which soldiers over a few years were commonly using. By April 2011, project manager Colonel Charles Wells announced version 3 of the Army system (code named "Griffin") was being deployed in the US war in Afghanistan. In January 2012, the United States Army Communications-Electronics Research, Development and Engineering Center hosted a meeting based on the DCGS-A early experience. It brought together technology providers in the hope of developing more integrated systems using cloud computing with open architectures, compared to previously specialized custom-built systems. A major contractor was Lockheed Martin, with computers supplied by Silicon Graphics International out of its Chippewa Falls, Wisconsin office. Software known as the Analyst's Notebook, originally developed by i2 Limited, was included in DCGS-A. IBM acquired i2 in 2011. Some US Army personnel reported using a Palantir Technologies product to improve their ability to predict locations of improvised explosive devices. An April 2012 report recommending further study after initial success. Palantir software was rated easy to use, but did not have the flexibility and wide number of data sources of DCGS-A. In July 2012, Congressman Duncan D. Hunter (from California, the state where Palantir is based) complained of US DoD obstacles to its wider use. Although a limited test in August 2011 by the Test and Evaluation Command had recommended deployment, operation problems of DCGS-A included the baseline system was "not operationally effective" with reboots on average about every 8 hours. A set of improvements was identified in November 2012. The press reported some of the shortcomings uncovered by General Genaro Dellarocco in the tests. The ambitious goal of integrating 473 data sources for 75 million reports proved to be challenging, after spending an estimated $2.3 billion on the Army system alone. In May 2013 Politico reported that Palantir lobbyists and some anonymous returning veterans continued to advocate the use of its software, despite its interoperability limits. In particular, members of special forces and US Marines were not required to use the official Army system. Similar stories appeared in other publications, with Army representatives (such as Major General Mary A. Legere) citing the limitations of various systems. Congressman Hunter was a member of the House Armed Services Committee which required a review of the program, after two other members of congress sent an open letter to Secretary of Defense Leon Panetta. The Senate Defense Appropriations Subcommittee included testimony from Army Chief of Staff General Ray Odierno. The 130th Engineer Brigade (United States) has found the system to be "unstable, slow, not friendly and a major hindrance to operations". The equivalent system for the United States Navy was planned for initial deployment by 2015, and within a shipboard network called Consolidated Afloat Networks and Enterprise Services (CANES) by 2016. Some early testing was announced in 2009 aboard the aircraft carrier USS Harry Truman. A portion of the software, a distributed data framework for the DCGS integration backbone (DIB) version 4, was submitted to an open-source software repository of the Codice Foundation on GitHub. The framework was new for DIB version 4, replacing the legacy DIB portal with an Ozone Widget Framework interface. It was written in the Java programming language. == DCGS-A == Distributed Common Ground System-Army (DCGS-A) is the United States Army's primary system to post data, process information, and disseminate Intelligence, Surveillance and Reconnaissance (ISR) information about the threat, weather, and terrain to echelons. DCGS-A provides commanders the ability to task battle-space sensors and receive intelligence information from multiple sources. === Promotion === An August 17, 2011, UPI article quoted i2 Chief Executive Officer Robert Griffin who commented on DCGS-A's best-of-breed approach to development. The article detailed the Army contracting with i2 for Analyst's Notebook software. "With its open architecture, Analyst's Notebook supports the Army's strategy to employ and integrate best-of-breed solutions from across the industry to meet the dynamic needs users face in the field on a daily basis." A February 1, 2012, article in the Army web page quoted Mark Kitz, DCGS-A technical director. DCGS-A "uses the latest in cloud technology to rapidly gather, collaborate and share intelligence data from multiple sources to deliver a common operating picture. DCGS-A is able to rapidly adapt to changing operational environments by leveraging an iterative development model and open architecture allowing for collaboration with multiple government, industry and academic partners." A July 2012 article in SIGNAL Magazine, monthly publication of the Armed Forces Communications and Electronics Association, promoted DCGS-A as taking advantage of technological environments with which young soldiers are familiar. The article quoted the DCGS-A program manager, Col. Charles Wells on the systems benefits. The article also included Lockheed Martin's DCGS-A program manager. The Milwaukee Journal Sentinel published an article May 4, 2012, about Wisconsin-located companies helping DCGS-A with cloud computing technology. The article promoted the speed when cloud computing processes intelligence and cost savings by analyzing data in the field. === The U.S. Army's 2011 Posture Statement === The U.S. Army released its 2011 Army Posture Statement March 2. It included a statement on DCGS-A: “The Distributed Common Ground System-Army (DCGS-A) is the Army's premier intelligence, surveillance, and reconnaissance (ISR) enterprise for the tasking of sensors, analysis and processing of data, exploitation of data, and dissemination of intelligence (TPED) across all echelons. It is the Army component of the larger Defense Intelligence Information Enterprise (DI2E) and interoperable with other Service DCGS programs. Under the DI2E framework, USD (I) hopes to provide COCOM Joint Intelligence Operations Centers (JIOCs) capabilities interoperable with DCGS-A through a Cloud/widget approach. DCGS-A connects tactical, operational, and theater-level commanders to hundreds of intelligence and intelligence-related data sources at all classification levels and allows them to focus efforts of the entire ISR community on their information requirements. === Comparisons === Some Ground Commanders who describe DCGS-A as "unwieldy and unreliable, hard to learn and difficult to use," supporting alternative software from Palantir Technologies. Palantir software supports small unit situational awareness, but is not sufficiently funded to support the broader role that DCGS-A fulfills. == Operators == 480th Intelligence, Surveillance and Reconnaissance Wing 9th Intelligence Squadron 13th Intelligence Squadron 548th Intelligence, Surveillance and Reconnaissance Group 548 Operational Support Squadron 48th Intelligence Squadron 101st Intelligence Squadron 113th Air Support Operations Squadron 127th Command and Control Squadron 161st Intelligence Squadron
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Freemake Video Converter

Freemake Video Converter is a freemium video editing app developed by Ellora Assets Corporation. Designed primarily for entry-level users, the software offers a range of functionalities including video format conversion, DVD ripping, and the creation of photo slideshows and music visualizations. Additionally, Freemake Video Converter is capable of burning video streams that are compatible with various media, such as DVDs and Blu-ray Discs. It also features direct video uploading capabilities to platforms like YouTube., enhancing its utility for content creators. The application's user-friendly interface and broad compatibility make it accessible for individuals with minimal video editing experience. == Features == Freemake Video Converter can perform simple non-linear video editing tasks, such as cutting, rotating, flipping, and combining multiple videos into one file with transition effects. It can also create photo slideshows with background music. Users are then able to upload these videos to YouTube. Freemake Video Converter can read the majority of video, audio, and image formats, and outputs them to AVI, MP4, WMV, Matroska, FLV, SWF, 3GP, DVD, Blu-ray, MPEG and MP3. The program also prepares videos supported by various multimedia devices, including Apple devices (iPod, iPhone, iPad), Xbox, Sony PlayStation, Samsung, Nokia, BlackBerry, and Android mobile devices. The software is able to perform DVD burning and is able to convert videos, photographs, and music into DVD video. The user interface is based on Windows Presentation Foundation technology. Freemake Video Converter supports NVIDIA CUDA technology for H.264 video encoding (starting with version 1.2.0). == Important updates == Freemake Video Converter 2.0 was a major update that integrated two new functions: ripping video from online portals and Blu-ray disc creation and burning. Version 2.1 implemented suggestions from users, including support for subtitles, ISO image creation, and DVD to DVD/Blu-ray conversion. With version 2.3 (earlier 2.2 Beta), support for DXVA has been added to accelerate conversion (up to 50% for HD content). Version 3.0 added HTML5 video creation support and new presets for smartphones. Version 4.0 (introduced in April 2013) added a freemium "Gold Pack" of extra features that can be added if a "donation" is paid. Starting with version 4.0.4, released on 27 August 2013, the program adds a promotional watermark at the end of every video longer than 5 minutes unless Gold Pack is activated. Version 4.1.9, released on 25 November 2015 added support for drag-and-drop functions that were not available in prior versions. Since at least version 4.1.9.44 (1 May 2017), the Freemake Welcome Screen is added at the beginning of the video, and the big Freemake logo is watermarked in the center of the whole video. This decreases the quality of free outputs, and users are forced to pay money to remove the watermark or stop using it. Version 4.1.9.31 (11 August 2016) does not have this restriction. == Licensing issues == FFmpeg has added Freemake Video Converter v1.3 to its Hall of Shame. An issue tracker entry for this product, opened on 16 December 2010, says it is in violation of the GNU General Public License as it is distributing components of the FFmpeg project without including due credit. Ellora Assets Corporation has not responded yet. == Bundled software from sponsors == Since version 4.0, Freemake Video Converter's installer includes a potentially unwanted search toolbar from Conduit as well as SweetPacks malware. Although users can decline the software during installation, the opt-out option is rendered in gray, which could mistakenly give the impression that it's disabled.
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Human visual system model

A human visual system model (HVS model) is used by image processing, video processing and computer vision experts to deal with biological and psychological processes that are not yet fully understood. Such a model is used to simplify the behaviors of what is a very complex system. As our knowledge of the true visual system improves, the model is updated. Psychovisual study is the study of the psychology of vision. The human visual system model can produce desired effects in perception and vision. Examples of using an HVS model include color television, lossy compression, and Cathode-ray tube (CRT) television. Originally, it was thought that color television required too high a bandwidth for the then available technology. Then it was noticed that the color resolution of the HVS was much lower than the brightness resolution; this allowed color to be squeezed into the signal by chroma subsampling. Another example is lossy image compression, like JPEG. Our HVS model says we cannot see high frequency detail, so in JPEG we can quantize these components without a perceptible loss of quality. Similar concepts are applied in audio compression, where sound frequencies inaudible to humans are band-stop filtered. Several HVS features are derived from evolution when we needed to defend ourselves or hunt for food. We often see demonstrations of HVS features when we are looking at optical illusions. == Block diagram of HVS == == Assumptions about the HVS == Low-pass filter characteristic (limited number of rods in human eye): see Mach bands Lack of color resolution (fewer cones in human eye than rods) Motion sensitivity More sensitive in peripheral vision Stronger than texture sensitivity, e.g. viewing a camouflaged animal Texture stronger than disparity – 3D depth resolution does not need to be so accurate Integral Face recognition (babies smile at faces) Depth inverted face looks normal (facial features overrule depth information) Upside down face with inverted mouth and eyes looks normal == Examples of taking advantage of an HVS model == Flicker frequency of film and television using persistence of vision to fool viewer into seeing a continuous image Interlaced television painting half images to give the impression of a higher flicker frequency Color television (chrominance at half resolution of luminance corresponding to proportions of rods and cones in eye) Image compression (difficult to see higher frequencies more harshly quantized) Motion estimation (use luminance and ignore color) Watermarking and Steganography
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Apache CarbonData

Apache CarbonData is a free and open-source column-oriented data storage format of the Apache Hadoop ecosystem. It is similar to the other columnar-storage file formats available in Hadoop namely RCFile and ORC. It is compatible with most of the data processing frameworks in the Hadoop environment. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. == History == CarbonData was developed at Huawei in 2013. The project was donated to the Apache Community in 2015 submitted to the Apache Incubator in June 2016. The project won top honors in the BlackDuck 2016 Open Source Rookies of the Year's Big Data category. Apache CarbonData has been a top-level Apache Software Foundation (ASF)-sponsored project since May 1, 2017.
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Bring your own encryption

Bring your own encryption (BYOE), also known as bring your own key (BYOK), is a cloud computing security model that allows cloud service customers to use their own encryption software and manage their own encryption keys. == Overview == BYOE enables cloud service customers to utilize a virtual instance of their encryption software alongside their cloud-hosted business applications to encrypt their data. In this model, hosted business applications are configured to process all data through the encryption software. This software then writes the ciphertext version of the data to the cloud service provider's physical data store and decrypts ciphertext data upon retrieval requests. This approach provides enterprises with control over their keys and the ability to generate their own master key using internal hardware security modules (HSM), which are then transmitted to the cloud provider's HSM. When the data is no longer needed, such as when users discontinue the cloud service, the keys can be deleted, rendering the encrypted data permanently inaccessible. This practice is known as crypto-shredding. == Potential Advantages == Organizations can store data with unique encryption that only they can access. Multiple organizations can share the same hardware infrastructure via cloud services like Amazon Web Services (AWS) or Google Cloud while maintaining encryption to comply with regulations such as HIPAA. == Potential Challenges == Resource utilization may be higher compared to traditional encryption practices when multiple users share the same hardware and use their own encryption. Efforts to minimize resource utilization issues may potentially impact security benefits.
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Ibotta

Ibotta, Inc. is an American mobile technology company headquartered in Denver, Colorado. Founded in 2011, the company offers cash back rewards on various purchases through its Ibotta Performance Network and direct to consumer app. Ibotta partners with CPG (consumer packaged goods) brands and network publishers to provide these rewards. As of 2024, the company operates solely in the United States. The company's rewards-as-a-service offering, the Ibotta Performance Network, went live in 2022. In August 2019, Ibotta received a $1 billion valuation after its Series D funding, and in 2023, the company surpassed $1.5 billion cash rewards paid to over 50 million consumers since the company's founding. Ibotta became a publicly traded company in April 2024 with a listing on the New York Stock Exchange. As of September 2025, Ibotta is trading at approximately $27.13 per share, marking a 69% decline from its initial public offering price of $88 per share on April 18, 2024. == History == === Founding through early 2019 === Ibotta was founded by current CEO Bryan Leach. The company was incorporated in 2011 and the app launched to both the App Store and Google Play stores in 2012. Early investors included entrepreneur and computer scientist Jim Clark and Tom “TJ” Jermoluk, Chairman of @Home Network. In 2015, Ibotta expanded beyond item level grocery, adding the ability to get cash back on in-store retail purchases. In 2016, in-app mobile commerce began, allowing users to navigate from the Ibotta app to its partners' apps to earn cash back on purchases. In 2016 with a Series C investment, Ibotta had raised over $73 million in funding. In March of that year, Ibotta partnered with Anheuser-Busch to offer cash back for adults who purchased its products. In May, the company partnered with LiveRamp so that companies could use their CRM data to create segmented, personalized campaigns. At the time, the company had around 200 full- and part-time employees and moved from offices in Lower Downtown Denver (LoDo) to a 40,000-square-foot office in the central Denver business district. A year later, the company had to expand to a second floor as it added almost another 100 employees. In 2017, Ibotta added cash back for Uber to its app as well as cash back rewards for online and mobile purchases. In 2018, Ibotta was listed on the Inc. 5,000 list as one of the fastest growing private companies in the U.S. A year later, in January 2019, the Ibotta app had been downloaded more than 30 million times with users receiving a reported $500 million in cash back rewards. That year, Ibotta was the largest mobile company in Colorado with six million monthly active users. === August 2019 to present === In August 2019, Ibotta was valued at $1 billion, following a Series D round of funding. The round was led by Koch Disruptive Technologies, a subsidiary of Koch Industries. 2019 was also the year the company introduced Pay with Ibotta, which allowed users to complete purchases at key retailers on the Ibotta app and earn instant cash back in the process. With that new service, users were able to enter their purchase total and use a QR code to checkout and receive immediate cash back. In 2020, the company partnered with Trees for the Future to plant up to 1 million trees as part of an Earth Month campaign to raise awareness about the waste of unused paper coupons. In response to the COVID-19 pandemic, Ibotta partnered with CPG brands in their “Here to Help” campaign and together committed over $10 million in cash back to American consumers. The company added the ability to earn cash back from online grocery pick-up and delivery orders. Later that year, Ibotta started its free Thanksgiving program, providing users with 100% cash back on select groceries needed for a Thanksgiving meal. By 2022, the company had provided approximately 10 million Thanksgiving meals. In 2021, Ibotta acquired the company OctoShop (originally InStok), a shopping browser extension company. The OctoShop app enables users to compare prices across stores and set restock and price-drop alerts. In April 2022, the Ibotta Performance Network (IPN) was launched. The IPN allows brands to deliver digital offers to consumers through third party publishers. Retailers including Walmart, Dollar General and Family Dollar, food delivery services including Instacart, and convenience stores including Shell are all part of the Ibotta Performance Network. This pay-per-sales or success-based performance network reaches over 200 million consumers. On April 18, 2024, Ibotta had its initial public offering (IPO), trading on the New York Stock Exchange (NYSE) under the ticker symbol IBTA. It was the largest technology IPO in Colorado history. In October 2025, Ibotta announced a partnership with technology and analytics company Circana, integrating Circana's Household Lift measurement into Ibotta campaigns to give CPG brands an increased understanding of the impact of their promotional campaigns. On November 3, 2025, Ibotta launched LiveLift, a tool for companies to measure the return on investment of digital promotions, in order to optimize performance marketing goals. === Athletic partnerships === Ibotta became the official jersey patch partner of the New Orleans Pelicans, a professional men's basketball team in the National Basketball Association (NBA), for the 2020–2021 and 2023–2024 seasons. Ibotta became the official jersey patch partner of the 2023 NBA champion Denver Nuggets baskeetball team beginning in the 2023–2024 season. In March 2023, F1 driver Logan Sargeant, the first U.S. racer to compete in F1 since 2015, partnered with Ibotta. The Ibotta logo was displayed on Sargeant's racing helmet throughout his F1 career. In June 2023, UConn Huskies women's basketball player Paige Bueckers entered into a "name, image, and likeness" (NIL) promotional agreement with Ibotta. According to a press release by Ibotta, the company has agreements with The Brandr Group, which finds NIL opportunities for women college athletes, and the Pearpop social media marketing platform to promote Ibotta. == Legal issues == In April 2025, shareholders filed a class action lawsuit—Fortune v. Ibotta, Inc., in the U.S. District Court for the District of Colorado (Case No. 25-cv-01213)—alleging that the registration statement in connection with Ibotta’s April 2024 initial public offering omitted material information. The complaint claims that, although Ibotta disclosed detailed terms for its contract with Walmart Inc., it failed to warn investors that its agreement with The Kroger Co., its second-largest client, was terminable at will and thus could be canceled without warning, creating a misleading impression of stability.
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Protocol Builder

Protocol Builder is a tool in programming languages to generate code to build protocols in a fast and reliable way. Network programming for all kinds of protocols (such as TCP, UDP, and SNMP) includes converting data to be transferred to raw bytes in the sending side and parsing these bytes in the receiving side. Protocol builders facilitate this stage, usually by automatically generating the code. Protocol Programming has many components to be developed, these are: server listener, server connection, client connection, packets, and loggers. Most protocol builders implement these components automatically so developers save time and money. Currently, there are two Protocol Builders in the market, one for C++ from UpRedSun which is for TCP and UDP protocols. The second one is for .Net languages which generates the code in C# for TCP Protocols, this tool is called .Net Protocol Builder.
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Toggl Track

Toggl Track (formerly Toggl) is a time tracking software developed by Toggl OÜ which is headquartered in Tallinn, Estonia. The company offers online time tracking and reporting services through their website along with mobile and desktop applications. Time can be tracked through a start/stop button, manual entry, or dragging and resizing time blocks in a calendar view. == History == According to Alari Aho, Toggl's CEO and founder, the application has been fully self-funded from the start. The name was created using a random name generator.
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Skipper (computer software)

Skipper is a visualization tool and code/schema generator for PHP ORM frameworks like Doctrine2, Doctrine, Propel, and CakePHP, which are used to create database abstraction layer. Skipper is developed by Czech company Inventic, s.r.o. based in Brno, and was known as ORM Designer prior to rebranding in 2014. == Overview == Generates visual model from the schema definition files Repetitive import/export of schema definitions in supported formats (XML, YML, PHP annotations) Schema definition files are automatically generated from the visual model Visual representation uses ER diagram extended by concepts of inheritance and many-to-many Supports customization using .xml configuration files and JavaScript Does not support direct connections to the database Crude and simplistic visual representation and menus == Architecture == Skipper was built on the Qt framework. Import/export of the schema definitions uses XSL transformations powered by LibXslt library. Imported source files are first converted to XML format: no conversion for XML, simple conversion for YML, creating the Abstract Syntax Tree and its subsequent conversion to XML for PHP annotations. The import/export scripts are configured in JavaScript and can be freely customized. == Supported ORM frameworks == Frameworks supported for visual model and schema files generation: Doctrine2 Doctrine CakePHP == History == Skipper was created as an internal tool for the web applications developed by Inventic. It was first published as a commercial tool under the name ORM Designer in 2009. Application was reworked and optimized in January 2013, and released as ORM Designer 2. In May 2013 ORM Designer became part of the South Moravian Innovation Center Incubator program (support program for innovative technological startups). In June 2014, ORM Designer version 3 was released and rebranded under the name of Skipper
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IruSoft

IruSoft (Arabic: آيروسوفت) is an insurance regulatory platform designated for licensing, supervision and inspection of the insurance sector within a country. The platform introduced unique supervision-technology (suptech), insurance-technology (insurtech) and regulatory-technology (regtech) automated modules by which a regulator requires less resources to ensure fairness, transparency and competition and to prevent conflicts of interest in the sector. IruSoft was founded by Abdullah Al-Salloum and owned by the Insurance Regulatory Unit in Kuwait. The Insurance Regulatory Unit optimized processing insurance-sector's customer complaints by issuing Resolution No. (1) of 2022 that introduced IruSoft's complaints public module; an automated resolution center, by which the process of receiving submitted complaints, passing them on to the platforms of licensed insurance companies, tracking matter-related discussions and updates and getting them escalated if unresolved to be discussed by a committee assigned by the unit is integrally automated and analyzed for better key performance indicators.
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The Most Dangerous Writing App

The Most Dangerous Writing App is a web application for free writing that combats writer's block by deleting all progress if the user stops typing for five seconds. It is targeted at creative writers who want to write first drafts without worrying about editing or formatting. == Features == The app is designed to "shut down your inner editor and get you into a state of flow", referring to the psychological concept of being in a flow state. Users start a writing session by choosing a time or word limit, and can only save or download their work if they complete the set limit without interruption. An optional "hardcore mode" blurs out everything the user has written so far, making it impossible to edit before finishing the writing session. == History == The Most Dangerous Writing App was created by software engineer Manuel Ebert and was released as free, open source software on February 29, 2016. It was reviewed by Wired, Forbes, Vogue, Huffington Post, The Verge, The Next Web, and others. It has been used in free writing contests and is recommended by NaNoWriMo. In April 2019, The Most Dangerous Writing App was acquired by Squibler, but the original version remains freely accessible.
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Cloud-based design and manufacturing

Cloud-based design and manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are able to configure products or services and reconfigure manufacturing systems through Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Hardware-as-a-Service (HaaS), and Software-as-a-Service (SaaS). Adapted from the original cloud computing paradigm and introduced into the realm of computer-aided product development, Cloud-Based Design and Manufacturing is gaining significant momentum and attention from both academia and industry. Cloud-based design and manufacturing includes two aspects: cloud-based design and cloud-based manufacturing. Another related concept is cloud manufacturing that is more general and popular. Cloud-Based Design (CBD) refers to a networked design model that leverages cloud computing, service-oriented architecture (SOA), Web 2.0 (e.g., social network sites), and semantic web technologies to support cloud-based engineering design services in distributed and collaborative environments. Cloud-Based Manufacturing (CBM) refers to a networked manufacturing model that exploits on-demand access to a shared collection of diversified and distributed manufacturing resources to form temporary, reconfigurable production lines which enhance efficiency, reduce product lifecycle costs, and allow for optimal resource allocation in response to variable-demand customer generated tasking. The enabling technologies for Cloud-Based Design and Manufacturing include cloud computing, Web 2.0, Internet of Things (IoT), and service-oriented architecture (SOA). == History == The term cloud-based design and manufacturing (CBDM) was initially coined by Dazhong Wu, David Rosen, and Dirk Schaefer at Georgia Tech in 2012 for the purpose of articulating a new paradigm for digital manufacturing and design innovation in distributed and collaborative settings. The main objective of CBDM is to further reduce time and cost associated with maintaining information and communication technology (ICT) infrastructures for design and manufacturing, enhancing digital manufacturing and design innovation in distributed and collaborative environments, and adapting to rapidly changing market demands. In 2014, the same research group also published the worldwide first two books on the subjects of Cloud-Based Design and Manufacturing (CBDM) and Social Product Development (SPD) with Springer, edited by Dirk Schaefer. == Characteristics == CBDM exhibits the following key characteristics: Cloud-based distributed file system High performance computing Cloud-based social collaboration Ubiquitous access to distributed big data Rapid manufacturing scalability Agility On-demand self-service Semantic Web Real-time request for quotation Pay-per-use pricing model Multi-tenancy CBDM differs from traditional collaborative and distributed design and manufacturing systems such as web-based systems and agent-based systems from a number of perspectives, including (1) computing architecture, (2) data storage, (3) sourcing process, (4) information and communication technology infrastructure, (5) business model, (6) programming model, and (7) communication. == Service models == Infrastructure as a service (IaaS) Platform as a service (PaaS) Hardware as a service (HaaS) Software as a service (SaaS) Similar to cloud computing, CBDM services can be categorized into four major deployment models: the public cloud, private cloud, hybrid cloud, and community cloud. == Research progress in Academia == The Defense Advanced Research Projects Agency (DARPA) MENTOR program Engineering and Physical Sciences Research Council cloud manufacturing program European Commission's Seventh Framework Program (EC FP7)
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