TigerGraph

The Fortune 50 company, one of the largest technology corporations in the world, was seeking to develop a new core customer 360 record system. This system was intended to offer a product recommendation system and entity resolution feature. The goal was to create accurate customer profiles that displayed hierarchical relationships, thereby delivering an exceptional customer experience when customers interacted with their centralized database for various functions such as purchasing products or requesting services. The company also desired a system that was scalable and more efficient than their previous one. This operational function for their customer 360 was deemed critical to their competitive advantage in the market. The system was to consist of a centralized data source that would serve as the core of the customer data platform.

A leading cybersecurity company, known for its threat intelligence, endpoint protection, and disaster recovery services, was facing a significant challenge. The company was unable to scale their classification services with their existing SQL Server-based solution. The rapid emergence of new websites necessitated the use of accurate and timely threat data, and the execution of thousands of classifications per second across massive data sets. The company recognized the need for a completely new back-end to power their classification services, to keep pace with the ever-expanding internet.

The financial institution, one of the largest in the United States, was seeking to enhance its networking and link analysis capabilities for anti-money laundering. The institution wanted to identify connections between open work items in situations of interest, such as previous SAR filings and other open work items, and make this information available to analysts and investigators. They also wanted to conduct thorough ad hoc reviews of an entity, displaying the connections from an ecosystem surrounding a specific starting point of an investigation. Furthermore, the system should enable analysts to identify which connections and situations of interest lead to productive investigations and inform the creation, hibernation, or escalation of work items. The company was in search of a solution that offered a client-focused approach, state-of-art technology, and a next-generation database management solution that integrated seamlessly with its existing workflow.

Sightline Systems offers a real-time operations intelligence solution focused on analytics, root-cause analysis, performance management, correlation of data and predictive analysis from any source — critical IT systems including mainframes, applications, storage, databases — down to the process level. Sightline’s powerful analytics go beyond point-in-time data to include over time and real-time trend analysis, with abnormal behaviours or events dynamically communicated for appropriate actions. For more than 10 years Sightline has reported a 95% renewal rate from customers including Fortune 500 and Global 2000 companies in finance, telecommunications, travel, and retail as well as federal, state and local governments.

Dashmote is a Dutch company specialized in AI market intelligence solutions primarily using Image Recognition, NLP and other Data Mining techniques to analyze data in online and e-commerce platforms around the world. We provide our clients with real-time, online information regarding their brand, outlets universe and industry trends as well as any other aspect of their business that can be analyzed with algorithms.In 2018, we won Best B2B Startup in Europe by McKinsey, Google and Rocket Internet. This year opened our Asia offices in Shanghai. Some of our global clients include companies such as Coca-Cola, Unilever, and Heineken among many more.General deck: https://docsend.com/view/4chsy88

Inspection? was incubated inside Sky-Futures and spun out prior to the sale of Sky-Futures to Private Equity in May 2019. The founding team have worked together for an average of 4 years in Sky-Futures before the launch of Inspection?.Our core competence is solving deeply technical problems and making them available to enterprise customers through a scalable and configurable application. We understand the requirements of large enterprise companies and the realities of Industrial data collection, a workflow that manages the organisation and analysis of TBs of data and the integration into existing platforms and applications.

DataFactZ is a Data Analytics company focused on enabling data-driven transformation. DataFactZ supports many leading data and analytics platforms and has solid partnerships with many tech providers. They combine several Data Science techniques from statistics, Machine Learning, deep learning, decision science, cognitive science and business intelligence, offering solutions such as data management, predective analytics and data engineering to businesses.

Industrial data platformThe ConnectedThinks Industrial data platform is capable of connecting to multiple industrial data sources, correlating and transforming the data into useful insights, and helping improve the efficiency of your industrial business.Edge ConnectorsThe edge-connectors suite is a middleware deployable on ARM or X86-based Industrial edge IoT gateways. It enables quick connection and rapid onboarding of various assets such as machinery, sensors, asset trackers, Bluetooth beacons, and IP Video streams as well as OT assets such as PLC, SCADA, CNC, and HMI – to name a few. It offers secure device management and remote connection. Data PlatformThe ConnectedThinks data platform is a modern technology stack, built-to-scale to ingest and process high-speed, high-density, and real-time industrial data. Its functionality could be split into 3 primary parts – the data-ingest, the data-transform-&-store, and the data-query part.The data-ingest part consists of a high-performant MQTT broker and a highly-scalable, multi-cluster Kafka messaging queue which together can ingest and process data at a very high speed.The data-transform-&-storage part is built on top of Kafka KSQLdb and Apache Spark with real-time data transformation and the ability to integrate real-time machine-learning predictions for Anomaly Detection and other Predictive Maintenance tasks. The platform offers out-of-the-box connectors to store data on almost any database, data warehouse, or even into S3-storage compatible Data Lakes with efficient storage formats like PARQUET and AVRO.The data-query part consists of multiple custom-built connectors to various SQL and pseudo-SQL databases and storages along with highly-scalable PRESTO (a.k.a prestodb)Together it forms a complete Industry 4.0 offering for data intelligence and integration. The entire offering is built with Microservices and dockerized to make it suitable for deployment on-prem, private-cloud, or Public Cloud like AWS, Azure, or Google. Data visualization & BIConnectedThinks platform offers a custom-built visualization engine, built from the ground up to serve the specific requirements of industrial operations which demand a combination of real-time diagnostic monitoring for high-speed data, a SCADA-like monitoring system with visual aids and historical data analytics with data ranging from a few weeks to couple years. It is built on top of front-end REACT-js libraries along with Authentication and fine-grain access Authorization to deliver a secure web portal that is accessible from any corner of the world. The platform is also pre-integrated with Apache Superset and offers embedded dashboards as well as quick drag-and-drop data exploration. The prestodb query engine ODBC connectors enable you to import and explore data from your existing BI solutions such as Tableau, Looker, PowerBI, etc,