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Finance teams don’t need another system to learn. They need their existing tools to work better. That’s the core idea behind Next Generation Disclosure Management from insightsoftware — insightsoftware’s narrative reporting solution that plugs directly into Microsoft Word and Excel, bringing live data, built-in controls, and a full audit trail into the environment your team already knows by heart. No new interfaces. No copy-paste marathons.

Get AI-generated reports that explain why your metrics changed, not only what happened, using connected live data, specific prompts, and a six-step process.

The tech world woke up to a major shock when a notorious hacking group, TeamPCP, claimed it had broken into GitHu b’s internal systems. The group is currently selling access to roughly 4,000 of GitHu b's private code repositories on cybercrime forums, demanding a massive $50,000 ransom. If GitHub, the platform holding the code for 100 million developers worldwide, can get hacked through a single employee's workstation, what does that mean for your business?

Pull session feedback, survey responses, and behavioral signals into your warehouse, CRM, or AI pipeline, fully transformed, on schedule, with no engineering required. Mouseflow is one of the most-loved tools for understanding how people actually use your website. Session replays, heatmaps, feedback surveys, and funnel analysis give product, marketing, and CX teams a window into real user behavior, the kind of insight that doesn't show up in event analytics or quantitative dashboards.

Over-the-air (OTA) updates are one of the most powerful tools available to React Native teams. The ability to push changes directly to users’ devices without App Store review, without Google Play approval, without any action required from the user, meaningfully changes how fast a team can respond to bugs and iterate on their product. But OTA updates operate within clear boundaries. Misunderstanding those boundaries leads to two distinct problems.

At Qlik Connect, one question kept coming up in conversations with leaders: “Which AI vendor should we pick?” But I think that’s the wrong starting point. The better question is: What kind of company do you want to become over the next three years? Right now, most organizations are heading down one of two paths with AI. Some are bolting it onto existing workflows to improve efficiency.

Customer relations excel when support teams can access knowledge at scale.

Customers today face significant challenges as their Kubernetes environments scale. The proliferation of microservices, external integrations, and new AI workloads increases traffic volume and connectivity complexity, creating material risks to performance and availability. The core issue is a lack of end-to-end governance: as diverse workloads expand, unmanaged interactions make it difficult to apply consistent security and enforce global consumption policies.

Retail banking is quietly undergoing one of its biggest shifts in decades. Customers no longer compare banks to other banks. They compare them to Netflix, Amazon, and every digital experience that already gets them. That expectation has changed the game. This is where AI-powered personalization in retail banking comes in. Instead of offering generic products to broad customer segments, banks can now deliver hyper-relevant experiences in real time.

According to SmartBear’s Closing the AI Software Quality Gap study, 93% of teams are already using AI to generate code. The same study found that 60% expect AI to produce nearly half of all code within the next year. This shift in development velocity is already impacting software testing and quality. Most teams say application quality is suffering, and 60% have experienced quality issues in the past year because development is moving faster than testing can keep up.