AI TECH

Algolia Announces the Release of an AI-Based Recommendation API, Algolia Recommend

Algolia | July 01, 2021

Algolia, the leading API platform for Dynamic Experiences, announced today the general availability of Algolia Recommend, a high-performance, AI-optimized API that speeds the development and execution of product recommendations across digital touchpoints.

The Vegan Kind, a provider of vegan subscription boxes, is all about assisting consumers in making the correct decisions by providing them with excellent options and recommendations while they explore. In addition, the Vegan Kind was able to display suggested products associated with the items seen after installing Algolia Recommend, boosting the potential for shopping cart growth.

Algolia Recommend uses machine learning models to surface the most relevant recommendations, offers, or suggestions for a shopper in milliseconds, using data from two sources: shopper behavior (the shoppers' actions throughout a website or app, including previous purchases) and product data (all product attributes contained in the product catalog, including product, description, availability, and price).

The API-first approach, front-end frameworks, and advanced documentation of Algolia Recommend ensure that it is easy to integrate and extremely adaptable. HiCart, the developer of a user-friendly, Lebanese marketplace enabling its members to have a smooth experience, was having trouble providing suggestions with their existing solution. HiCart integrated Algolia Recommend and went live in four days with as few as six lines of code. When consumers search for a particular item, other alternatives are now shown, giving customers more choices, a more satisfying experience, and a lower chance of abandoning their shopping cart.

Algolia Recommend boosts average order value (AOV) in online stores by expanding shopping carts and improving customer satisfaction. Businesses can quickly raise their average order value using Algolia Recommend's smart "related product" feature, which increases their ability to merchandise a wider variety of goods. As a result, they can provide highly relevant suggestions, showing a more profound knowledge of their customers and earning more loyalty in the process.

Algolia Recommend, which is now available, combines two of the most popular machine learning models for automatically delivering customized recommendations:

Related Products: This recommendation model helps businesses improve conversions and orders by analyzing items customers engage with (e.g., clicks, adds to cart, and purchases) throughout their sessions and recommending related products based on this data.

Frequently Bought Together: This recommendation model boosts AOV by upselling complementary products on the product page or shopping basket page based on what other consumers bought with that exact item during a single shopping session.

About Algolia
Algolia offers an API platform for Dynamic Experiences, allowing businesses to predict intent and provide outcomes. Algolia achieves this through an API-first approach that enables developers and business teams to surface relevant content when required — satisfying the demand for instant gratification and building and optimizing online experiences that improve online engagement, increase conversion rates, and enrich lifetime value to generate profitable growth. Algolia is used by over 10,000 companies, including Under Armour, Lacoste, Birchbox, Stripe, Slack, Medium, and Zendesk, to handle over 1.5 trillion search requests each year. Algolia's headquarters are in San Francisco, and the company has offices in Paris, London, Tokyo, New York, and Atlanta.

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AI APPLICATIONS

Veryfi Reports 750% Year-Over-Year Growth in AI-Driven Intelligent Document Processing Platform Use

Veryfi | August 17, 2022

Veryfi, using artificial intelligence (AI) technology to instantly transform documents into structured data, today announced that the company has seen 750% year-over-year growth in the Veryfi OCR API Platform usage. This follows a successful Intelligent Automation Week event in Chicago, where Veryfi announced its momentum in powering the world’s leading finance, ERP (enterprise resource planning), and accounting software providers. The growth of Veryfi’s OCR API Platform usage signals that companies are seeing better time-to-value with Intelligent Document Processing (IDP), rather than Robotic Process Automation (RPA) alone. Additionally, IDP solutions with pre-trained AI outperform home-grown solutions built using commodity OCR and AI tooling, in terms of accuracy and time-to-value. IDP delivers the most accurate data extraction technology, providing the fastest time to value and greatest efficiency. Over the past five years, Veryfi’s AI-Driven OCR API Platform with Day 1 Accuracy* was pre-trained on hundreds of millions of documents of all types, for 85 currencies, 39 languages, and 110 data fields. “Our AI-driven IDP solution is the first to promise Day 1 Accuracy with no humans in the loop, and our customers’ growing trust in our platform is a clear sign that we’re living up to that promise. “We’re absolutely thrilled that our customers are joining us on our mission to eliminate manual data entry, and are seeing increased efficiency, revenue, and time to value, starting on Day 1, with our platform.” Ernest Semerda, co-founder and CEO of Veryfi RPA isn’t an out-of-the-box AI solution; as a standalone solution, it requires implementation and training that dramatically delays a business' time to value. When RPA is coupled with Veryfi IDP, however, customers benefit from pre-trained AI that delivers Day 1 Accuracy and perfectly complements the enhanced automation capabilities of RPA solutions. With Veryfi, enterprises can accelerate financial document processing by 200 times, with significantly fewer errors than humans can achieve, and companies can more effectively comply with the increasing number of international security and privacy regulations. According to the Everest Group, “Many organizations are devoting more financial and human resources to deploy intelligent document processing capabilities. Success by forward-looking organizations is driving confidence in a market expected to grow 70-80% over the next two years to US $1.1 billion.” By eliminating manual data entry, Veryfi enables organizations to accurately capture, extract and transform documents such as receipts, invoices, purchase orders, checks, credit cards, and W-9 forms into structured data, at scale. Veryfi uses advanced AI/ML technology, trained by hundreds of millions of documents over the past four years, to extract data and transform it into a structured format for 85 currencies, 39 languages, and 110 defined fields such as vendor, total, bill to/ship to, purchase order and invoice numbers, any line item (product name, SKU, description), taxes, and more, which can then be accessed for a wide variety of business applications. About Veryfi Veryfi empowers organizations to capture, extract and transform unstructured documents including receipts, invoices, purchase orders, checks, credit cards, and W-2s into structured data at scale. The company’s technology reduces or eliminates manual data entry and unlocks valuable business intelligence in seconds. Trusted by enterprises and software companies alike, Veryfi’s AI-driven platform delivers fast, accurate, and secure data to hundreds of companies globally.

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AI TECH,GENERAL AI

Hyperspec AI Releases Software Platform for Autonomous Driving Development

Hyperspec AI | September 15, 2022

Hyperspec AI, an artificial intelligence startup, released a new tool for developers working on ADAS enabled and autonomous vehicles (AV). The company has developed a unified platform called RoadMentor that allows users to create, train, and deploy machine-learning (ML) models for real-time mapping. Hyperspec integrates the map into the ML training loop so that real-time mapping models can be developed, giving ADAS enabled and autonomous vehicles the ability to perform outside of the HD map geofence. This expands navigable roads from less than 5% today to over 95%, for any vehicle, so the autonomous systems can learn from the ubiquitous exposure. Today, the ML development process is fragmented with no integrated process for data collection, data management, model training, verification & validation, deployment, and fleet learning. Each step is another data transfer, leading to inefficiency and a lack of true visibility. RoadMentor enables the industry to scale through deep learning by consolidating the loop training process into one optimized infrastructure designed specifically for autonomous driving. "We wanted to create a product that focuses on our customers' pain points. RoadMentor streamlines data flow, drastically reducing processing time, standardizes data throughout the cycle, and moves data access and control in-house rather than with a third-party. Sravan Puttagunta, CEO and co-founder of Hyperspec Autonomous driving data is largely skewed towards highway and arterial road domains. The release of RoadMentor increases test coverage from less than 5% to over 95% across all roads, enabling edge case library build out across the long tail of scenarios. Now ADAS functionality and autonomous driving usage and coverage can further develop allowing us to reach levels 3, 4, and 5 autonomy. "We're very excited about the progress we have made in recent months," says Puttagunta, "right now it's all about collecting usable test miles and collating good data to improve the system. Solving the long-tail problem is something we have been thinking about for a long time." RoadMentor is offered as a freemium SaaS product, so users can process a certain amount of data at no cost. We invite developers to sign up for exclusive beta access to RoadMentor through our developer program, limited seats are available. Attendees of the International Auto Show Tech Days will be able to learn first-hand how RoadMentor improves the release cadence of autonomous driving technology development.

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SOFTWARE,FUTURE TECH,COMPUTER VISION

Datawiza Integration with Microsoft 365 Brings MFA to Oracle Business Applications

Datawiza | September 19, 2022

Datawiza, the industry's leading cloud-native access proxy for securing applications, today announced a new integration with Microsoft 365 that allows businesses to deploy multifactor authentication (MFA) for mission-critical Oracle business applications. By creating a no-code, secure bridge between Oracle applications and Microsoft 365, the Datawiza cloud-native proxy enables Microsoft 365 customers to quickly extend the power of Microsoft's modern Identity and Access (IAM) solution, Azure Active Directory , to Peoplesoft, Oracle E-Business Suite, JD Edwards (JDE) and Siebel – in minutes. Datawiza: Modern Access Management for Hard-to-Secure Applications “Thousands of enterprises today run on business applications that don’t always support modern security protocols,” said Dr. Canming Jiang, Co-Founder & CEO of Datawiza. “Corporate boards are demanding immediate action to eliminate vulnerabilities, but replacing mission-critical applications like Peoplesoft, E-Business Suite, JDE and Siebel would take far too long and cost too much. Our cloud-native proxy helps organizations extend their investment in these solutions by enabling modern capabilities like MFA and single sign-on in less than five minutes, helping them quickly respond to new security requirements, such as the need to meet cyber insurance requirements or establish Zero Trust Application Access.” “Microsoft is passionate about helping businesses protect their identities, applications, and data. “Datawiza is a partner in our Secure Hybrid Access program. Their fast, secure solution helps our customers take advantage of the multifactor authentication capabilities built into Azure AD (now part of Microsoft Entra) to protect their portfolio of critical Oracle business solutions. This way, they can get even more value from their investment in Microsoft 365 and Microsoft Entra, our family of modern identity and access solutions.” Sue Bohn, Vice President of the Identity and Network Access Customer and Partner Experience Team at Microsoft Multifactor authentication adds an additional layer to application access, requiring users to prove their identity with more than just a username and password. When a user signs into an application, the system requires a second authentication, such as scanning a fingerprint or entering a code received by a smartphone. MFA is built into Microsoft 365, which includes Azure AD, but it relies on modern security protocols, such as SAML or OIDC, which Oracle and other legacy applications don’t support. The lightweight, cloud-delivered Datawiza platform relies on super-lightweight, cloud-native and container-based proxies located near the applications they protect. The Datawiza cloud-native proxy is deployed at the front end of the applications to create a bridge between the applications and Microsoft 365. In just a few minutes, Datawiza can be deployed and configured and begin requiring MFA, as well as single sign-on (SSO) and conditional access, to log into any application – from Oracle applications to homegrown applications to open source tools. The benefits of Datawiza include: Added security to extend the life of mission-critical investments – Datawiza works in all cloud, IAM and network infrastructures No-code, so quick to deploy – no security expertise required, no new vulnerabilities are inadvertently introduced Fine-grained access controls across homegrown, open source and legacy applications, for all environments: on-prem, cloud, multi-cloud, and hybrid Easily integrated with cutting-edge cloud-native technologies, such as containerization and Kubernetes Protection for individual applications even if the network is breached About Datawiza Datawiza, the industry's leading cloud-native access proxy for securing applications and APIs, provides consolidated and continuous risk and trust assessment. Unlike other access management products (e.g., legacy web access managers) that are complex and siloed in hybrid environments, Datawiza offers large enterprises and SMBs a comprehensive, centralized and easy-to-deploy solution that allows every company to simplify access management, save time and increase security. Datawiza was founded in 2018 by security expert Dr. Canming Jiang, a veteran of Shape Security, now part of F5, and cloud expert Cunhao (Alex) Gao, a veteran of Google and Amazon.

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SOFTWARE,FUTURE TECH

Spice AI Raises $13.5 Million Seed Funding to Enable Web3 Developers to Build Data and AI-driven Applications

Spice AI | September 08, 2022

Spice AI today announced a seed round of $13.5 million for its platform that enables developers to build data driven applications for Web3. Madrona led the round with Australia based Blackbird Ventures, Basis Set Ventures, Alumni Ventures Blockchain Fund, Joe McCann’s new Asymmetric fund, Protocol Labs, IEX Fund, and other strategic angel investors participating, including Thomas Dohmke, CEO of GitHub, who is also joining the board. “Spice AI is building a developer first platform to create AI/ML-driven applications that harness time series data – a valuable yet difficult to harness data set for any organization. There is no ecosystem out there that is more data rich than Web3 and blockchains, but that area is currently hampered by lack of data access and infrastructure. Solving the data problem in Web3 requires deep domain knowledge and Spice AI is building the infrastructure, so developers do not have to deal with the complexity of building it themselves. Now is the time to build for Web3 and we are excited to be well capitalized to grow the team and address this gap in the market,” said Luke Kim, CEO of Spice AI. Web3 and Spice AI While most blockchains are public and open, extracting data from them to power apps and ML is painfully difficult. To get meaningful quantities of useful data, developers are forced to build and operate a massively complex infrastructure which includes blockchain nodes, big data systems, ETL and ML pipelines, data lakes, data warehouses, and query systems. Going one step further, developers must deeply understand the various data sources including virtual-machine logs, and the inner workings and state of smart contracts, across a broad array of blockchains, scaling layers, and dApps. Spice.xyz, brings this together in a platform that enables developers to access web3 data across chains via SQL over high-performance Apache Arrow APIs. The platform is available in Preview today with Bitcoin, Ethereum, and Ethereum Name Service (ENS) datasets with work in progress to launch Solana and Polygon. “Madrona has invested in machine learning infrastructure and intelligent applications for almost a decade. We see a massive opportunity for Spice AI to provide a developer-first framework and intelligent data sets that unlock insights in blockchain data and enable developers to create intelligent distributed Web3 applications. As part of the financing, Porter will join the Spice AI board along with Thomas Dohmke. Tim Porter, Managing Director at Madrona Deeply Developer Focused Founders Over the last 15 years, co-founder Luke Kim has brought together the best builders and engineers across the globe to create developer focused experiences through tools and technologies used by millions worldwide. Before founding Spice AI, Luke was the founding manager and co-creator of Azure Incubations at Microsoft where he led cross-functional engineering teams to create and develop technologies like Dapr. Co-founder Phillip LeBlanc has spent a decade building some of the largest distributed systems and big data platforms used by millions worldwide. Before co-founding Spice AI, Phillip was both an engineering manager and IC working on distributed systems at GitHub and Microsoft. Phillip has contributed to services developers use every day including GitHub Actions, Azure Active Directory and Visual Studio App Center. “Spice AI is building the foundational platform for Web3, so developers do not have to invest in standing up their own infrastructure and in data engineering that is complex and costly, and frankly, hard to get right. Delivering real time insights from time-series data across chains powers intelligent applications being built for a wide range of industries – from addressing buying patterns in e-tail/retail all the way to fraud detection and securities trading. Since our pre-seed investment, the team continues to impress us with the focus and pace of innovation as they build this infrastructure for Web3,” added Aseem Datar, Partner at Madrona. Spice AI is building an office in greater Seattle with a footprint in Asia and Australia. Check out the positions here - spice.ai/careers About Spice AI Founded in June 2021 by Luke Kim and Phillip LeBlanc, Spice AI creates technology to help developers build intelligent apps that learn and adapt. The company has raised 14.5 million in funding since 2021 and is backed by leading venture and angel investors.

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