iOS 27 is Here. So is Day-Zero Support on Real Devices.
Every iOS team is about to hit a testing cycle they can't skip. And waiting until production is the expensive way to find out.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
iOS 27 Is Here: How Perfecto Keeps Your Apps Release-Ready
Apple's iOS 27 release marks another significant shift in the mobile landscape. Beyond new features for iPhone users, it signals a familiar pressure point for QA and development teams: the clock starts ticking the moment the update goes live, and your apps need to be ready. Here's why that matters: nearly 80% of iPhone users adopt the newest iOS version almost immediately. That high adoption rate leaves little room for error. If your app breaks on the iOS 27 release, your customers notice fast.
Automating Trust: How Business Review Management Fits Into the Modern Ops Stack
Most companies still treat reviews as a marketing chore. Someone on the team remembers, sends a batch of emails, watches a few stars roll in, and forgets about it for six weeks. That model is finished. Consumers now expect a reply within days, they discount anything written more than three months ago, and a growing share of them never read your reviews at all because an AI assistant read them first and summarized the themes. None of that can be served by a human remembering to check a dashboard.
Bring your test data into the AI tools you use | SmartBear MCP Server for Zephyr
Not everyone who needs a read on release readiness lives in Jira. This video demonstrates how the SmartBear MCP Server brings trusted Zephyr test data into Claude, so anyone who needs access to testing data gets it without switching context. A QE lead checking coverage, a release manager confirming a ship date, a developer following up on a fix, and any stakeholder who just wants a fast answer has what they need.
Test Management in the AI-Driven Era: What QA Teams Should Expect from Their Platform
Ask most QA teams how many tools it takes to manage one release and the list runs long: a repository for test cases, a separate grid for automated runs, a dashboard bolted on for reporting, and now an AI tool for generating or maintaining tests. Each has its own login, its own contract, and its own way of describing the same test case. That fragmentation is why "all-in-one test management platform" became the phrase buyers actually search for.
[Finance Demo] - AgentSpot Use Case - Virtual Card Spend Oversight
Manually cross-validating virtual card data across disconnected systems was a constant pain, until the procurement team built an AgentSpot agent to do it automatically. This video showcases a Virtual Card Intelligence agent that pulls PO and requisition data from Google Drive, cross-validates it against Spend Flow, flags expiring cards and utilization risks across 30/60/90 day bands, and sends personalized Slack outreach to card owners. Plus a full 9-tab Excel report covering KPIs, expiry, utilization, and reconciliation. The best part? This is all done in just 4-5 minutes.
[Finance Demo] AgentSpot Use Case - Procurement Automation: PR Approvals & Virtual Card Management
The procurement team at ThoughtSpot built two AgentSpot agents to tackle manual, time-consuming workflows — and the results speak for themselves. Agent 1 – Coupa PR Approval Nudger: Automated purchase requisition reminders that once took hours of manual chasing in Coupa and Slack. Approval cycle time dropped from 6.62 days to 2.8 days. Agent 2 – Virtual Card Intelligence: Cross-validates PO and requisition data against Spend Flow to surface budget leakage, flag expiring cards, and send personalized Slack outreach to card owners. All without manual audits.
[AgentSpot Showcase Series] Using AgentSpot to Automate Weekly Customer Status Updates
Every week, ThoughtSpot Engagement Manager MJ Densmore used to spend up to an hour per customer manually pulling notes, digging through Slack, and checking Salesforce — just to write a status update. Now, AgentSpot does it all automatically, pulling from meeting notes, Slack messages, and support cases to generate a concise summary she can review and send in minutes. Watch to see how a quick, single prompt does the work of a full hour.
The Smarter Safety Net: Modernizing User Acceptance Testing (UAT) with AI
Every engineering leader knows the scenario: sprint tickets are closed, unit coverage shows green across the board, API pipelines pass without a hitch, and the build is tagged "ready for release." Yet, the moment the software reaches actual business users, reality hits. A multi-tier approval workflow breaks on a regional tax calculation. An enterprise customer encounters friction during a custom bulk checkout.
Put Your Data to Work with ThoughtSpot in ChatGPT Work
Every organization says it wants self-service analytics, but very few have it. What actually stalls true self-service analytics is the invisible work that has to happen before anyone can ask a data question: the semantic layer, query engine, security model, and analytics app. That work lands on your product and data teams, who are already time-strapped to deliver core features and strategy, and it lands on them again every time a new question, a new tenant, or a new dashboard request arrives.