Pico acquired Redline Trading Solutions.
The addition of Redline’s high performance, multi-asset software solutions will provide access to a common API for global markets, both real-time and historical, delivered via Pico’s global network. The combined offering reduces complexity by allowing trading firms to optimize market access and coverage and trading stack performance in a seamless manner.
“As the trading environment becomes more globalized and continues to produce increasing amounts of data, clients are seeking greater efficiency in market infrastructure services and data consumption. Financial institutions want a trusted and globally comprehensive technology partner who understands their business, the market landscape and how to apply technology solutions. Combining Redline’s premier ultra-low latency trading and software solutions with Pico’s broad infrastructure, cloud and data offering, and industry leading Corvil Analytics, positions Pico uniquely to address these client needs and market challenges," said Jarrod Yuster, Chairman, Founder and Co- CEO of Pico.
Redline provides ultra-low latency software solutions and common APIs to over 180 global venues serving a marquee client roster that includes global banks, quantitative hedge funds, electronic trading firms, ETF market- makers and exchanges. Meeting the requirements of these clients and seamlessly adapting to their evolving needs in the future drive the mission and goals of both organizations.
Continued investments will extend the Redline service offering to become fully and globally comprehensive in delivering real-time and historical normalized financial market data including consolidated, delayed or end-of- day formats via wire protocol or API. Delivery will be available in Pico’s financial cloud, any remote location or into the public cloud. This will enable Pico’s clients to adopt a broad suite of common solutions in all regions delivered and supported by Pico’s global 24x7 operations and service model.
“I have admired Redline and what they have accomplished over the years,” continued Yuster. “Pico and Redline are aligned in our values, culture and expertise, and share a deep passion for meeting the needs of clients...There is a significant addressable market for global data consumption via software and a common API, and we will continue to invest in Redline further leveraging Pico’s global network and infrastructure coverage.”
“We have partnered on past initiatives, and we will now be able to access Pico’s globally deployed service organization, leading analytics and infrastructure footprint to scale our offerings to more geographies. We foresee great collaboration between our teams in the coming years in order to continue to meet clients’ evolving needs.” said Mark Skalabrin, Founder and CEO of Redline.
The acquisition will contribute to Pico’s growth strategy by adding Redline’s fully recurring revenue stream and high-margin business through increased client opportunity and a further expansion of in-house expertise. It follows the successful integration of Corvil Analytics, the best-in-class financial markets trade monitoring and performance platform1, which extended Pico’s expertise into analytics and data science.
Financial terms of the transaction were not disclosed. Redline had previously been backed by GS Growth, the growth investing arm of Goldman Sachs.
Jefferies LLC acted as exclusive financial advisor and DLA Piper served as legal advisor to Pico in connection with the transaction. Broadhaven acted as exclusive financial advisor and Davis Malm served as legal advisor to Redline in connection with this transaction.
The Latest
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...