Systems | Development | Analytics | API | Testing

AI Workspace + Cursor: Generating a consistent test base from your code

Prompting your agentic IDE to write tests gives you different steps and different results every time. The result is inconsistent and low-quality test cases. Combine AI Workspace's agentic workflows with your Cursor IDE to generate a consistent, reusable test base straight from your code repository. In this walkthrough, Product Marketing SVP Ryan Yackel will show how Tricentis generates test cases from a GitHub repo, stores them in qTest, and runs tests against a desktop application.

Hot Sauce Releases - Better Together: Meet Sauce Labs AURA

AI-generated code is growing exponentially. Verified releases are growing linearly. AURA (AI-Unified Release Assurance) is Sauce Labs' agentic AI platform that closes that gap: authoring, running and analyzing tests at AI speed, with human oversight, inside the tools your team already uses. In this on-demand session, Steven Spadaccini and Trent Yoxall walk one control plane through four doors.

Top Banking-as-a-Service (BaaS) Providers in 2027

‍ Banking-as-a-Service (BaaS) enables fintech companies to integrate regulated banking capabilities through APIs and licensed banking partners. These capabilities include account management, payment processing, card issuance, and embedded financial services. Selecting reliable banking as a service providers is becoming increasingly important as regulatory scrutiny and operational risks reshape the industry.

The Control Tower Reaches into the Runtime: Announcing the ServiceNow and Kong Partnership

Today ServiceNow launched the **ServiceNow Control Tower Alliance**, and Kong is proud to be a founding member to help enterprises put AI to work safely, at scale. It's a milestone for Kong, and we think it's an important moment for the industry. Here's what the alliance is, why it matters, and why we believe every AI control tower needs a runtime. Enterprise AI has moved from pilots to production faster than most governance programs could keep up.

Agentic Data Stewardship: Qlik Demo

Agentic Data Stewardship keeps a human in charge while agents do the legwork. Agents use data profiling results and validation rules to proactively identify data quality issues and recommend fixes, and your data stewards can decide which fixes to approve or refine each action before they are applied. The result is higher stewardship productivity, more accurate data, and a shorter proactive path from raw data to something people can trust and use, while meeting governance.

AI Needs to Know What Your Data Means, and Whether to Trust It

Over the past year, nearly every data and analytics vendor has made the same argument: AI agents need business context. Give a model enterprise data without telling it how the business defines revenue, margin, or an active customer, and it will give confident answers to the wrong questions. I agree. But definitions alone are not enough.