Corvil, innovator of electronic trading and market data latency management systems, today announced Thomson Reuters Markets division as a new client of CorvilNet, the company's core software platform.
CorvilNet monitors, analyzes and optimizes electronic trading and market data applications against ultra-low latency objectives. Corvil, with operations in New York, London and Dublin, serves a global client base spanning exchanges; alternative trading platforms; proprietary trading groups; investment banks; broker-dealers; high-frequency and automated market making trading firms; hedge funds; and market service providers.
"Thomson Reuters Markets is dedicated to ensuring its global client base experiences end-to-end latency that will not exceed specified levels and we are confident CorvilNet will perform a crucial role in managing this ongoing process," said Corvil CEO, Donal Byrne.
Thomson Reuters will use CorvilNet to manage a range of services and applications carried across their next generation global backbone network. CorvilNet's unique feature set will allow Thomson Reuters to identify and eliminate latency bottlenecks, in addition to reducing the time and money spent diagnosing and fixing latency problems. In particular, Corvil's support of SLA compliance will enable Thomson Reuters to assure the speed and quality of their services proactively, in a complex and dynamic environment.
"Our business demands the lowest possible latency in an ever growing traffic environment," said Thomson Reuters Markets Global Head of Wide Area Network Engineering, Ayman Soliman. "We have chosen CorvilNet to help us optimize the global infrastructure and provide real time analytics in order to meet the business demands."
CorvilNet enables clients to specify and report against precise latency and loss SLAs (service level agreements) for intra- and inter-party application flows; deploy microsecond monitoring for applications and service channels across networks; troubleshoot violations through automated event capture and root-cause analysis; and leverage real time data of anomalies in applications, networks and resource requirements into a more efficient and competitive electronic trading value proposition.