Skip to main content

Pico Launches Corvil Cloud Analytics

Pico has expanded the reach and visibility of Corvil Analytics into the cloud with the launch of Corvil Cloud Analytics.

Pico’s Corvil Analytics has a 20-plus year legacy across financial services in extracting and correlating technology and transaction performance intelligence from global dynamic network environments. Corvil’s high throughput, lossless, granularly time-stamped data capture provides an incredibly rich data source that can be used for broader analytics and use cases, including trade analytics. Corvil is available across multiple environments including colocation and on-prem, and now those same attributes are available in the cloud with Corvil Cloud Analytics.

“As companies look to move real-time applications to the cloud, they struggle with visibility when utilizing existing cloud monitoring solutions,” said Stacie Swanstrom, CPO at Pico. “There is a need for deeper visibility to fill those voids, and Corvil Cloud Analytics is the solution...Corvil Cloud Analytics provides our clients with the real-time analytics required to migrate their most critical workloads to the cloud, with confidence.”

Highlights of Corvil Cloud Analytics include:

- Maximum Visibility: Measures every order, every market data tick and every packet to fill the missing gap of visibility needed to manage real-time performance in public cloud environments

- Granular Instrumentation: Provides per-packet and per-application message analytics alongside Corvil’s AppAgent to instrument internal application performance

- Corvil Analytics: Provides all functions of Corvil Analytics including network congestion analytics for public cloud infrastructure, and per-hop trading and market data analytics for cloud-hosted deployments

- Flexibility: Pay for only what is needed in the public cloud

With the launch of Corvil Cloud Analytics, and as exchanges partner with the major cloud providers to bring trading into the cloud, Corvil can now provide a single pane of glass for monitoring colocation, on-prem and cloud environments together.

“We had the vision to provide clients the same technology, visibility and rich analytics they’ve come to rely on through Corvil,” Swanstrom said. “Since Corvil Cloud Analytics is software only, this accelerates our deployments and also provides an expedited avenue for proof-of-concept use cases. It’s now easier than ever for clients to access the platform so they can see firsthand what makes Corvil an industry leader in data analytics.”

Corvil Cloud Analytics provides the highly granular, real-time Corvil visibility required to understand the cause of variable performance that continues to impact real-time applications running in the public cloud. With cloud applications, there is no hardware CapEx costs, lead times, or shipping and installation challenges. Corvil Cloud Analytics is simple to scale, easy to deploy and can be up and running in hours instead of weeks. Corvil’s visibility and intelligence is now available for businesses wanting the competitive edge in the cloud.

The Latest

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

In a 2026 survey conducted by Liquibase, the research found that 96.5% of organizations reported at least one AI or LLM interaction with their production databases, often through analytics and reporting, training pipelines, internal copilots, and AI generated SQL. Only a small fraction reported no interaction at all. That means the database is no longer a downstream system that AI "might" reach later. AI is already there ...

In many organizations, IT still operates as a reactive service provider. Systems are managed through fragmented tools, teams focus heavily on operational metrics, and business leaders often see IT as a necessary cost center rather than a strategic partner. Even well-run ITIL environments can struggle to bridge the gap between operational excellence and business impact. This is where the concept of ITIL+ comes in ...

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...

Pico Launches Corvil Cloud Analytics

Pico has expanded the reach and visibility of Corvil Analytics into the cloud with the launch of Corvil Cloud Analytics.

Pico’s Corvil Analytics has a 20-plus year legacy across financial services in extracting and correlating technology and transaction performance intelligence from global dynamic network environments. Corvil’s high throughput, lossless, granularly time-stamped data capture provides an incredibly rich data source that can be used for broader analytics and use cases, including trade analytics. Corvil is available across multiple environments including colocation and on-prem, and now those same attributes are available in the cloud with Corvil Cloud Analytics.

“As companies look to move real-time applications to the cloud, they struggle with visibility when utilizing existing cloud monitoring solutions,” said Stacie Swanstrom, CPO at Pico. “There is a need for deeper visibility to fill those voids, and Corvil Cloud Analytics is the solution...Corvil Cloud Analytics provides our clients with the real-time analytics required to migrate their most critical workloads to the cloud, with confidence.”

Highlights of Corvil Cloud Analytics include:

- Maximum Visibility: Measures every order, every market data tick and every packet to fill the missing gap of visibility needed to manage real-time performance in public cloud environments

- Granular Instrumentation: Provides per-packet and per-application message analytics alongside Corvil’s AppAgent to instrument internal application performance

- Corvil Analytics: Provides all functions of Corvil Analytics including network congestion analytics for public cloud infrastructure, and per-hop trading and market data analytics for cloud-hosted deployments

- Flexibility: Pay for only what is needed in the public cloud

With the launch of Corvil Cloud Analytics, and as exchanges partner with the major cloud providers to bring trading into the cloud, Corvil can now provide a single pane of glass for monitoring colocation, on-prem and cloud environments together.

“We had the vision to provide clients the same technology, visibility and rich analytics they’ve come to rely on through Corvil,” Swanstrom said. “Since Corvil Cloud Analytics is software only, this accelerates our deployments and also provides an expedited avenue for proof-of-concept use cases. It’s now easier than ever for clients to access the platform so they can see firsthand what makes Corvil an industry leader in data analytics.”

Corvil Cloud Analytics provides the highly granular, real-time Corvil visibility required to understand the cause of variable performance that continues to impact real-time applications running in the public cloud. With cloud applications, there is no hardware CapEx costs, lead times, or shipping and installation challenges. Corvil Cloud Analytics is simple to scale, easy to deploy and can be up and running in hours instead of weeks. Corvil’s visibility and intelligence is now available for businesses wanting the competitive edge in the cloud.

The Latest

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

In a 2026 survey conducted by Liquibase, the research found that 96.5% of organizations reported at least one AI or LLM interaction with their production databases, often through analytics and reporting, training pipelines, internal copilots, and AI generated SQL. Only a small fraction reported no interaction at all. That means the database is no longer a downstream system that AI "might" reach later. AI is already there ...

In many organizations, IT still operates as a reactive service provider. Systems are managed through fragmented tools, teams focus heavily on operational metrics, and business leaders often see IT as a necessary cost center rather than a strategic partner. Even well-run ITIL environments can struggle to bridge the gap between operational excellence and business impact. This is where the concept of ITIL+ comes in ...

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...