Let’s talk AUTO XLR8
Purpose-built automation for investment management workflows, connected data and the change that keeps coming.
AUTO XLR8 + DQ
One connected investment lifecycle.
AUTO XLR8 / WORKFLOW
An order enters an order management system, often from another application. Testing needs to follow that instruction beyond the point where it is created.
DQ / DATA INTEGRITY
Do account, instrument and order details remain consistent as the instruction enters the next system?
AUTO XLR8 / WORKFLOW
Compliance checks sit within a wider investment process. Their behavior needs to be considered alongside the systems, permissions and data on which they depend.
DQ / DATA INTEGRITY
Are the records used for compliance checks accurate, consistent and correctly mapped across the workflow?
AUTO XLR8 / WORKFLOW
Orders pass to an execution management system and execution details return. Cross-system testing considers that round trip, including the handoff between platforms.
DQ / DATA INTEGRITY
Do the data returned from execution correspond to the instruction and retain the information needed downstream?
AUTO XLR8 / WORKFLOW
Execution details feed allocation workflows. The sequence must remain coherent as the information passes between teams and applications.
DQ / DATA INTEGRITY
Do quantities, accounts and positions reconcile as records are translated or transformed?
AUTO XLR8 / WORKFLOW
Information moves onward to accounting systems or a custodian. Testing the full chain helps expose dependencies that a single-system check cannot see.
DQ / DATA INTEGRITY
Does the information reaching accounting or the custodian remain accurate and reconcilable with its source?
AUTO XLR8 / WORKFLOW
Reporting draws on the operation that precedes it. Assurance connects the complete workflow with its data, rather than treating arrival at an endpoint as sufficient evidence.
DQ / DATA INTEGRITY
Are the reported records complete and consistent with the underlying systems, transformations and reconciliation checks?
THE COMPLETE TESTING CYCLE
A single investment instruction crosses order management, compliance, execution, allocation, settlement and reporting. Each step brings different teams, permissions and data. Coordinating that chain manually can take weeks; under delivery pressure, comprehensive testing is often reduced.
Auto XLR8 brings those checks into a repeatable process. Pre-built, domain-specific actions reflect the behavior of platforms such as Charles River, Aladdin and Bloomberg, so teams can assemble relevant workflows without starting from a blank page.
Cover functional and regression testing, integration, data analysis, validation and reconciliation. Performance testing spans batch data, business workflows and the end-user experience under realistic load.
An Excel-based experience lets non-technical users add scenarios as rows and run tests without writing scripts. Engineering teams can extend the platform with Python and C# and integrate it with CI/CD pipelines.
Run on a schedule, on demand or after code updates. Carry scenarios through development, system integration testing (SIT) and user acceptance testing (UAT), with controlled production-monitoring use cases where appropriate.
See what passed, what failed, how much the system can handle and when performance changed. Pre-trading morning reports give senior stakeholders a clear view of the latest validation results, while reducing repeated UAT demands on portfolio managers, traders and compliance teams.
DQ / DATA QUALITY
DQ compares databases, APIs, flat files, Excel and ETL outputs, including sources that use different formats and definitions. It maps them to a common model and reconciles individual records at volumes that can reach millions, beyond a practical spreadsheet-based review.
The checks examine accuracy, consistency and formatting, as well as whether records match. Diagnostic capabilities help investigate possible explanations, including a corporate action, stock split or change to a vendor file.
Describe a workflow in plain language. Auto XLR8 uses existing actions and knowledge of investment systems to construct it, giving practitioners a foundation to refine and validate.
Testing history—scenarios executed, system performance, failures and their causes—supports diagnostic intelligence and the team’s knowledge graph. This accumulated experience helps practitioners investigate issues and develop subsequent workflows.
BEYOND A SINGLE RELEASE
Run repeatable checks on a schedule, on demand or after code changes. Reuse scenarios across development and UAT, with controlled production-monitoring use cases where appropriate.
Explore a proof of conceptVelocity typically starts with a proof of concept using your systems and data. The team will discuss your environment, objectives and an appropriate scope before any commitment to delivery.
Velocity works alongside your team, vendors and partners. Automation supports repeatable validation, while practitioners contribute domain understanding, implementation expertise and interpretation of results.
We begin with your workflows, connected systems and assurance priorities. A guided demonstration shows how Auto XLR8 and DQ support those needs; a scoped proof of concept can then explore the fit using your own environment and data.
THE BUSINESS CASE
The practical objective is to run broader checks more frequently, identify issues while they are less costly to address and give decision-makers evidence for go-live. A proof of concept uses your systems and data to establish what that could mean for your environment before a larger commitment.
Test more of your operation, more often. Auto XLR8 reduces repetitive manual work and gives your team more time to focus on the decisions that need their expertise.
A manual testing effort involving 30–40 people can become an automated operation run by one or two, with broader coverage and more frequent validation. By year five, total testing cost can be approximately 18% of a traditional manual program.
AI can take on the hardest 80% of workflow construction, giving your specialists more time to refine scenarios, investigate exceptions and improve coverage.
Results depend on your systems, testing scope and delivery model. Start with a proof of concept to assess the value for your operation.
Explore the business case for your teamYOUR NEXT CHAPTER
Tell us what’s changing, where the uncertainty sits,
and what your team needs to achieve.