BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT, DATA SCIENCE
Pico | January 27, 2023
Pico is one of the global leaders in providing mission-critical technology services, software, data and analytics to the financial markets. While its Corvil Analytics is best known for ensuring the performance of low-latency electronic trading systems, Corvil VoIP Analytics is used to oversee the operations and performance of some of the world's biggest and most complex VoIP installations. To make sure that VoIP is reliable and of good quality, the Corvil method of evaluating network and application activity at the same time is essential.
Chief Product Officer at Pico, Stacie Swanstrom, said, “With 20 years of experience in deriving operational intelligence from demanding and dynamic networks, Corvil Analytics has established a critical role in high-performance trading environments.” She added, “Corvil VoIP Analytics takes the ability to capture and decode lossless granularly timestamped data at 100GB and applies it to VoIP applications, providing the same rich data clients have come to expect in both on-prem and cloud deployments.”
(Source – GlobeNewswire)
One significant advantage of Corvil's wire data technique is that it offers a vendor-agnostic method of managing VoIP quality. Large enterprises often rely on several suppliers, and depending on vendor-bundled diagnostic tools provides only a partial and fragmented picture. In addition, 60% of current Corvil VoIP consumers have switched suppliers in the last three years. Corvil was important to the success of those initiatives, and it also provided a complete picture before, during, and after the migration.
The Corvil solution's value is centered on quick and easy access to rich analytics:
A unified interface for summary VoIP performance dashboards highlighting overall KPIs and failure rates
When troubleshooting difficulties with providers and suppliers, complete packet capture for each call gives a clear record
Drill-down into individual calls with a single click and quick access to both signaling messages and the voice call packet stream
Splunk, Orion, Nagios, and other third-party operations management systems benefit from extensive open APIs and live streaming of key metrics
About Pico
Pico is one of the leaders in providing technological services to the financial market sector. Its technology and services are used for mission-critical power systems for worldwide banks, exchanges, electronic trading businesses, quantitative hedge funds, and financial technology service providers. The firm offers a best-in-class array of market solutions that are creative, transparent, and low-latency, as well as an agile and expert service delivery methodology. PicoNet™, a globally comprehensive network infrastructure instrumented natively with Corvil to provide analytics and telemetry, offers instant access to financial markets. Pico is chosen by clients that desire the ability to react quickly and gain an operational advantage in the fast-paced world of financial markets.
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BIG DATA MANAGEMENT, BUSINESS STRATEGY, DATA SCIENCE
Tredence Inc. | January 17, 2023
On 16 January 2023, Tredence, a global data science and AI solutions provider, announced the launch of an intelligently engineered platform, ATOM.AI. The platform is an end-to-end AI accelerator that accelerates data and analytics modernization.
The announcement to launch ATOM.AI was made at the National Retail Federation (NRF), the leading retail industry show, for retailers and consumer goods companies.
ATOM.AI assists industries in data transformation into winning results by reducing the time to value by fifty percent. This is possible with the platform's advanced AI/ML capabilities, pre-built feature stores, technical notebooks, deep data sets, and integrations with third parties.
At NRF, Tredence will launch ATOM.AI, which powers the deployment and development of retail and CPG-centric AI applications 50% faster. The solution is built on the Databricks Lakehouse Platform.
ATOM.AI is a data and AI platform powered by leading hyperscales which consists of five modules designed to drive efficiency AI solution development and deployment phase
Data Works- to harmonize external and internal data and build a comprehensive feature store
Algo Works - to accelerate ML model development and enhance algorithm performance
UI/UX Works - to speed up application design with pre-built UI/UX templates
Solution Works - pre-built AI/ML solutions for large industries
Automation Works - integrates, orchestrates, deploys, and scales AI
Soumendra Mohanty, Chief Strategy Officer, Tredence, said, "Enterprises across all industries are examining ways to embed AI into their core business processes. However, only 53 percent of AI projects make it from prototype to production. In contrast to the previous technology transformations, AI is vastly different." He added, "We are dealing with a nonlinear condition here. ATOM.AI equips companies to put AI at the center of their transformation strategy while also delivering on our last-mile AI mission. With ATOM.AI, Tredence places a heavy emphasis on ROI."
(Source: PR NewsWire)
About Tredence
Tredence is a worldwide provider of data science solutions aiming to address AI's last-mile challenge. The gap between value realization and insight creation defines the last mile. Tredence has been acknowledged as a leader and a great place to work-certified in the Forrester WaveTM: Customer Analytics Services. The company is based in San Jose (California) and has offices in Foster City, Chicago, London, Toronto, and Bangalore.
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BIG DATA MANAGEMENT, BUSINESS STRATEGY, DATA SCIENCE
Arize AI | January 24, 2023
On January 23, 2023, Arize AI, an industry leader in machine learning observability, introduced a connection solution for BigQuery, Redshift, Delta Lake, and Snowflake data lakes. As a result, Arize customers with centrally managed inference stores can rapidly connect their ML table data to Arize via Data Lake Connectors for strong model observability.
Arize is the market leader in terms of both volumes of models and predictions tracked, surpassing billions of predictions daily. So far, ML observability platforms have struggled to simplify their deployments while simultaneously managing billions of predictions and complicated monitoring services, such as embedding drift. The latest Arize version for data connectors expands clients' connectivity options with the widely used data lakes.
The launch comes as the machine learning community converges on various MLOps designs. A modern machine learning architecture approach involves storing inference data in a data lake. ML teams are designing these ML data lakes to power feature stores for feature serving and an inference store for analysis.
Arize Data Lake Connectors are intended for smooth integration with today's data lake architectures. Among the benefits of connecting directly to the ML data store are the following:
Financial savings can be substantial as compared to alternative techniques of ML monitoring.
Teams can run off of an SSOT
Integration and onboarding are accelerated and simplified
Arize now connects with cloud storage providers (such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services), Python pipelines through an SDK, and Kafka Streaming. With this release, users of data lakes may get real-time model insights more efficiently than ever before. In addition, the platform provides fully managed built-in connectors as part of its cloud and VPC platform, eliminating the need for users to build and maintain complex data pipelines or use a separate ETL tool and providing real-time model performance analysis and monitoring.
About Arize AI
Arize AI offers an ML observability platform that monitors models and provides insights for troubleshooting production AI. The firm was established in 2020 in Berkeley, California. It allows corporate clients to monitor the performance of AI models using software that searches for unanticipated biases in algorithms, does root-cause analysis when issues arise, and enhances overall model performance. Arize operates in the background, analyzing internal and external data to forecast demand and eliminate supply chain network errors and sales losses. Adobe, Chick-fil-A, and eBay are among the fifty clients of Arize AI.
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