Systems | Development | Analytics | API | Testing

Customer support data is extremely valuable. Especially when integrated with other relevant sources, it can help users gain key business insights and better focus their marketing campaigns. Let’s take a look.

APIs are transforming how AI interacts with enterprise data. Instead of directly connecting AI to databases like MySQL, PostgreSQL, or MongoDB - which can lead to security risks, schema complexities, and high maintenance - APIs act as a secure middle layer. This approach simplifies data access, reduces risks, and ensures seamless integration with multiple databases.

Every year, Dresner Advisory Services publishes some of the most closely watched research in the enterprise performance management (EPM) space. Unlike analyst firms that rely heavily on vendor briefings, Dresner’s Wisdom of Crowds methodology gathers data directly from end users — the finance leaders, FP&A professionals, and CFOs who live inside these platforms every day.

Keep track of new connectors and product releases.

Over 1,000 people around the world tuned in as Tricentis CEO Kevin Thompson and VP of AI David Colwell unveiled our new integrated platform, followed by a live demo from Enterprise Solution Architect Matt Serpone. From our headquarters in Austin, Texas, we unveiled a unified solution designed to help enterprises treat quality as a coordinated system rather than a collection of disconnected tools.

Software testing has a bad rap for bottlenecks — and nowhere is that truer than in the SAP world. An overwhelming majority of SAP orgs continue to rely on manual testing practices that can consume up to 30% of implementation budgets, making QA out to be a persistent roadblock to transformation. To be fair to SAP QA teams, the issue is not as much about inefficiency as complexity.

Observability is the key to understanding and improving MCP servers. These servers connect AI agents to tools, but without visibility, issues like slow responses, errors, or security risks can go undetected. Observability helps track how agents interact with tools, pinpoint failures, and optimize performance.

Your data’s never lived in one place. Customer records might be in your CRM, while sales and operational metrics are split among data platforms. And somewhere, there's critical budget data living in a spreadsheet, owned by a single person on the finance team. Bringing it together has always come at a cost of speed vs. governance.

Performance testing without observability is like diagnosing a sick patient using only a thermometer. You get one number. You miss everything that matters. Observability-driven performance testing combines load testing with metrics, logs and distributed tracing to identify not just when performance degrades, but exactly why.

A clinical decision support tool suggests the wrong medication dose. A telehealth platform exposes 50,000 patient records. An AI diagnostics chatbot confidently gives incorrect test results. These are not just rare cases; they are real risks when healthcare software is released without proper HealthTech QA Services and healthcare software testing. Healthcare software cannot afford mistakes. In other industries, bugs can cause financial loss or inconvenience.