Atlassian announced it acquired Mindville, an asset and configuration management company based in Sweden. Mindville Insight provides enterprises with visibility into their assets and services, critical to delivering great customer and employee service experiences. Mindville will bolster Atlassian’s IT Service Management (ITSM) capabilities. By combining rich contextual information from disparate development tools with infrastructure-related information from Mindville, IT teams can now leverage Jira Service Desk to better anticipate the impact of changes to critical business services. Mindville is already a partner in the Atlassian Marketplace.
Mindville gives organizations a place to store and share information about all their assets and infrastructure across their whole business, even areas outside of IT such as HR, sales, and facilities. Teams can see how various services are linked to the underlying infrastructure, helping them understand how any given change will affect the customer or employee experience as a whole. Mindville also discovers and tracks assets and infrastructure by scanning the network, so teams don’t have to enter every asset manually. This solution integrates with cloud providers like AWS and Azure, and can either co-exist with, or help teams migrate away from, other solutions such as ServiceNow, Microsoft SCCM, and Snow Software.
Coveo announced that its cloud-native platform will be available in the commercetools Integration Marketplace to help provide personalized experiences for search and merchandising needs. Coveo provides the intelligence layer that enables organizations to deliver modern Ecommerce search, product recommendations, and personalization with relevant content. commercetools’ headless, API-first, multi-tenant SaaS commerce platform is cloud-native and uses microservices. The combination of the Coveo Experience Intelligence Platform and commercetools shopping features leverages modern API and microservices architectures to deliver relevant, contextual experiences powered by data that meet the expectations of modern Ecommerce buyers. Search re-orders products based on real-time customer data, delivers relevant content and integrates with any source of customer data.
Contentful announced a new Community Plan that provides those who build digital experiences with free access to Contentful’s content platform. Contentful’s community gain new technology capabilities, training and resources to build and launch digital experiences across all channels, including websites, mobile apps, wearable devices and digital displays. COVID-19 forced businesses to pivot their primary means of customer engagement to digital channels. Contentful is helping digital builders and businesses get started quickly by removing the friction of a software trial with a “free forever” plan and expanded educational resources. Builders can immediately start using the platform with free training, free certification and free use of Contentful’s tools forever — no 14 day trial or credit card needed.
Contentful is also making it easier for businesses to upgrade as they grow with a streamlined self-service Team plan and expanded Enterprise options. These offerings will make it easier for businesses to scale as they deliver content-driven digital experiences across more advanced use cases. Teams and small businesses can accelerate development on a self-service plan that enables them to start building for free and then upgrade based on their project needs with just a credit card. This offering includes expanded authoring roles and locales to support basic publishing workflows.
Unscrambl’s conversational analytics software ‘qbo insights’ is now available as qbo app for Microsoft Teams. qbo, by enabling natural language access to your data, makes facts and insights take center stage in workspace collaborations. With this addition Teams users can make fact-based decisions simply by conversing with their data. Unscrambl’s qbo leverages Teams’ capabilities for an interactive and collaborative data exploration experience. A business user would start by asking a question in natural language, as one would ask a human data analyst. The response is an interactive visualization of the requested data, often with a brief explanation, and suggestions about follow-up questions. Users can converse with qbo one-on-one or collaboratively as a team, view charts, refine, drill-down, create boards and even present their findings without having to leave the Teams platform.
Agility CMS is a content management system that allows marketing teams to create and manage content across their digital properties. Agility CMS provides tools that close the gap between monolithic traditional CMS platforms and pure developer-centric CMS tools that provides creative freedom for web developers while presenting familiar authoring tools to editors and content creators. Gatsby is a static site generator that allows users to create a static, HTML-based website that doesn’t rely on databases or external data sources at runtime, avoiding server-side processing when accessing your website. Static websites can be a hassle for content editors who have to regularly interact with the website codebase to make updates to content. That is where Agility CMS steps in: by providing a headless content management system for managing the content behind Gatsby in your static websites. Agility CMS provides native support for Gatsby and with Agility’s built-in Page Management, the plugin can automatically generate web pages based on a page tree defined in the CMS. This means editors can create their own pages, add and remove content on each page, and move things around on the sitemap without requiring assistance from a developer.
Box announced the addition of intelligent, automated classification to Box Shield, the company’s security solution for protecting content in the cloud. Leveraging machine learning, Shield can now automatically scan files and classify them based on their content, helping businesses detect and secure sensitive data without getting in the way of work. Box Shield helps prevent data leakage and proactively identifies potential insider threats or compromised accounts.
Using machine learning and data leakage prevention capabilities, this new feature scans files in real-time when they’re uploaded, updated, moved, or copied to specified folders, and automatically classifies them based on admin-defined policies. This enables customers to scale data classification and enforce policies across the enterprise, in order to reduce risk and meet compliance standards such as HIPAA, PCI DSS, and GDPR. Customers will be able to:
- Automatically identify multiple personally identifiable information types within files, including social security numbers, driver’s licenses, International Bank Account Number (IBAN) codes, International Classification of Diseases (ICD-9/ICD-10) codes, and more
- Automatically identify custom terms and phrases within files – for example: “Box Confidential”, “Internal use only”, and “NDA required”
- Easily create policies that apply the appropriate classification label based on desired logic – including and/or conditions and unique counts
Once files are classified appropriately, Shield can help prevent data leakage through a combination of access controls already in use by Shield customers, such as shared link, external collaboration, and download restrictions. The new feature supports the most common unstructured file types in Box, including documents, spreadsheets, PDF, Box Notes, and more. The new Box Shield automated classification capabilities will begin to be available today and will roll out to eligible customers over the next month.
Neofonie announced that TXTWerk – Text mining for SAP solutions, a framework application is now available for trial and online purchase on SAP App Center, the digital marketplace for SAP partner offerings. TXTWerk is delivered online as a subscription service and integrates with SAP and third-party software through the API management capabilities of SAP Cloud Platform Integration Suite. TXTWerk enables the extraction of metadata from texts, providing structured data from unstructured texts. By applying machine learning techniques in combination with rule-based approaches, TXTWerk can read and understand texts quickly. Whether 1,000 or 10 billion documents need to be processed, TXTWerk recognizes the most important keywords, people, places, organizations, events and key concepts and links them to sources such as knowledge graphs or internal company data. Also, part of the framework are artificial intelligence (AI) processes for classification in classes defined by the customer, a sentiment analysis of texts, phrase and role recognition as well as the automatic linking of entities according to specially defined relations. In addition to the AI processes, TXTWerk comes with a knowledge graph with over seven million entries.
Luminoso’s new deep learning model understands documents using multiple layers of attention, a mechanism that identifies which words are relevant to get context around a specific concept as expressed by a word or phrase. This model is capable of identifying the author’s sentiment for each individual concept they’ve written about, as opposed to providing an analysis of the overall sentiment of the document.
Using Concept-Level Sentiment, users will be able to:
- Effectively analyze mixed feedback — Concept-level sentiment analysis is critical for capturing and understanding the voice of the customer (VoC). For example, product reviews rarely contain just one type of feedback, and it’s important to tease apart the good from the bad. Getting a polarity for each of the topics in an open-ended survey response is critical for understanding what works and what doesn’t for your customers.
- Quickly surface buried feedback — Uncovering negative comments in overwhelmingly positive open-ended survey responses is critical for better understanding customers and employees. For instance, in voice of the employee (VoE) surveys, employee feedback can be overwhelmingly positive and delivered in an upbeat way in an effort to soften criticisms. Concept-Level Sentiment in Luminoso enables users to quickly identify and understand “buried” feedback, such as negative points in an overwhelmingly positive HR survey.
- Intuitively aggregate concept sentiment across an entire dataset — For instance, after responses to a mobile app market research survey are loaded into Luminoso Daylight, a user can get a distribution of positive, negative, and neutral opinions about every aspect of the mobile experience across all of its mentions in the dataset.
- Analyze customer and employee feedback across multiple languages — Global organizations often receive customer and employee feedback in multiple languages. With Luminoso, users can analyze the sentiment of concepts, natively in 15 languages.