Your weekly roundup of the most important QA, software testing, and software delivery launches for banks and financial services firms, as well as investments, partnerships, and other vendor news.
This week’s roundup ranges from agentic SAP testing and autonomous API mocking to synthetic data generation and AI hallucination detection, vendors are racing to close the widening gap between development velocity and software assurance.
SmartBear launches new AI test generation
SmartBear has launched a new AI test generation capability for ReadyAPI aimed at helping enterprises accelerate API testing while maintaining governance and application integrity.
The company said customers report ReadyAPI can “speed test creation by up to 80%” while still giving teams “complete control to enable or disable AI based on where they are in their AI journeys.”
“AI has accelerated code development velocity by 10X, but testing infrastructure has not kept up, creating a crisis that threatens application integrity across every organization,” explained Vineeta Puranik, CPTO at SmartBear, who sat down with QA Financial earlier this week. Read the interview here.
The launch comes as enterprises struggle to keep testing aligned with AI-assisted development velocity. SmartBear argued that many organisations are now facing a widening “testing debt” as development accelerates faster than validation cycles.
Holmes raises autonomous QA capital
Belgian startup Holmes has emerged from stealth with €1.1 million in pre-seed funding to build what it describes as an autonomous QA platform for software teams operating at AI development speed.
Based in Ghent, Holmes said its platform is designed to continuously generate and update tests automatically as products evolve, reducing dependence on manually maintained testing workflows.
The company was founded by Robin Praet, Robbrecht Delrue and Sofie Buyse, with funding led by Syndicate One alongside investors linked to the broader Ghent technology ecosystem. The funding will be used to expand engineering and product development as Holmes prepares broader rollout beyond its existing design partners.
Sofie Buyse, Product Manager at Holmes, pointed out that: “Testing frequently ends up on the plate of developers and product managers alongside their existing responsibilities. Holmes was built to automate that process and allow teams to continue shipping products with greater confidence.”
Parasoft brings MCP-powered API
Parasoft has introduced autonomous API mocking capabilities through a new Virtualize MCP server designed to eliminate dependency bottlenecks in distributed software delivery environments.
The release extends Parasoft’s AI-driven service virtualization technology into external LLM clients and AI agents, enabling “autonomous generation, deployment, and management of REST API mocks beyond the Virtualize UI.”
The company said the move is intended to support increasingly AI-native development workflows where developers rely heavily on tools such as GitHub Copilot, Claude Code and Codex.
The release also introduces autonomous workflows in which “AI agents invoke Virtualize MCP server tools to dynamically create and manage API mocks within build pipelines.”
According to the company, this allows test environments to remain aligned with rapidly evolving architectures while reducing delays caused by unavailable dependencies.
ASGN snaps up Quinnox
ASGN Incorporated has completed its acquisition of Quinnox, strengthening its digital engineering and offshore delivery capabilities as the company prepares to transition to the Everforth brand.
Quinnox’s global team will join ASGN’s Commercial Segment, adding expertise in application management, modernization, analytics and enterprise platforms.
“This strategic platform acquisition enhances our position in digital engineering and establishes a solid foundation for our offshore delivery capabilities,” explained ASGN CEO Ted Hanson.
The deal also expands ASGN’s India-based delivery operations alongside its existing nearshore capabilities in Mexico, supporting broader enterprise software and modernization services for commercial clients.
UiPath and Deloitte expand testing tie-up
UiPath and Deloitte have expanded their collaboration around agentic AI-driven software testing through Deloitte’s Ascend delivery platform.
The joint initiative combines UiPath Test Cloud with Deloitte Ascend to automate test design, reduce maintenance overhead and introduce self-healing execution capabilities. The companies said the platform enables “continuous autonomous quality” while integrating with existing enterprise infrastructure and processes.
According to the announcement, the platform “proactively detects changes, generates tests, and executes them autonomously,” allowing QA teams to focus more heavily on strategy and innovation rather than repetitive maintenance tasks.
UiPath said the collaboration embeds “1,500+ prebuilt testing bots and domain-specific AI agents” into the Ascend platform. The companies claimed this could deliver “up to 20% broader test coverage, 40% faster release cycles and 30% higher automation ROI.”
UST and K2view in synthetic test data tie-up
UST and K2view have announced a strategic partnership focused on synthetic data generation and AI-driven software testing. The companies said the collaboration aims to help enterprises overcome persistent bottlenecks around validation data, production data scarcity and AI model training.
Scott Owen, Global VP Partners and Alliances at K2view, stressed that “AI is changing the pace of software and model development, but enterprise data delivery has not kept up.”
K2view’s platform is already used by large enterprises across banking and other regulated sectors to deliver governed synthetic data environments. The announcement heavily emphasised the growing importance of data provisioning within AI-driven software delivery pipelines.
K2view’s platform combines AI-generated synthetic data with compliant real-world data “autonomously or conversationally” depending on enterprise requirements. The vendors argued that this enables organisations to “remove key data barriers across the AI lifecycle.”
Tricentis adds Agentic AI testing for SAP
Tricentis has introduced new AI-assisted automated test generation functionality for SAP Enterprise Continuous Testing by Tricentis, extending agentic testing deeper into SAP transformation projects.
The company said the new release enables organizations to generate automated SAP-compatible test cases directly within SAP Enterprise Continuous Testing using SAP AI Units. The functionality forms part of SAP’s broader “Agent-led toolchain.”
Tricentis argued that enterprises are facing mounting pressure to “deliver high quality software at the speed of AI while also managing an accelerating level of risk.” The company positioned the new capability as a way to reduce extensive manual effort while accelerating transformation programs.
SAP’s Karl Fahrbach added that the partnership would help customers “reduce manual effort, accelerate testing cycles, and maintain stability while navigating transformation.”
Kosli launches governance tool for AI delivery
Kosli has launched what it describes as governance infrastructure for AI-assisted software delivery, targeting financial services firms struggling to align compliance processes with AI-driven development velocity.
The company said legacy governance processes built around manual approvals and retrospective evidence gathering are increasingly incompatible with AI-assisted coding and DevOps pipelines. Kosli’s platform replaces these workflows with “policy-as-code, cryptographic evidence chains, and real-time compliance status.”
The launch has particular relevance for financial institutions under pressure to maintain auditability and governance while accelerating software delivery cycles. Kosli argued that manual governance “puts the brakes on software delivery, creating bottlenecks that cancel out the productivity gains AI is supposed to deliver.”
Kosli co-chairs the FINOS SDLC Common Controls Working Group alongside Deutsche Bank and Morgan Stanley, focusing on open standards for automated software governance in financial services.
Permutable AI develops financial info solution
London-based Permutable AI has launched a Developer Platform designed to transform unstructured information flows into AI-ready sentiment intelligence for financial markets.
The platform targets a growing challenge in AI adoption across trading, risk management and analytics: integrating fast-moving narrative and sentiment data into production-grade systems.
“AI systems are increasingly being used in environments where context changes quickly,” explained Wilson Chan, CEO and Founder of Permutable AI. “The challenge is making that information usable before it is reflected in structured datasets.”
Permutable said many AI systems remain overly dependent on “structured, historical datasets” while market-moving information flows remain difficult to operationalize in real time.
The company said the platform converts news flow, policy signals and market narrative into machine-readable outputs accessible through APIs and analytics pipelines.
“In many cases, market pricing is now adjusting to shifts in narrative hours or even days before those changes are reflected in structured datasets or official releases,” the company noted.
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REGULATION & COMPLIANCE
Looking for more news on regulations and compliance requirements driving developments in software quality engineering at financial firms? Visit our dedicated Regulation & Compliance page here.
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