Systems | Development | Analytics | API | Testing

Data activation maximizes the value of existing data infrastructure by reducing manual work, increasing reach, and enabling data teams to drive more strategic impact.

Modern innovation demands fast, secure, and flexible access to data. But when organizations deal with scattered databases and strict security policies, manual API development slows everything down. The solution? Automate how APIs are built, secured, and managed—using AI and open-source tools like DreamFactory.

A new MIT study reveals 95% of gen AI pilots fail. But that’s not an AI problem. It’s an implementation problem. The real issue is the messy, fragmented way AI is used. Too many organizations treat AI as a helper on the sidelines—chatbots, copilots, and assistants that wait to be called upon. While helpful, this approach barely scratches the surface of what’s possible. Real transformation happens when AI is embedded directly into the core operations of your enterprise.

Picture this: As you’re analyzing sales data in Qlik or in Power BI, you spot an obvious error in a customer name and think “I wish I could just fix this right here instead of sending another email to IT.” If this sounds familiar, you’re not alone. The good news is that the business intelligence (BI) world is finally listening. Gone are the days when BI platforms were solely for consuming and analyzing historical data.

At Koyeb, we run a serverless platform for deploying production-grade applications on high-performance infrastructure—GPUs, CPUs, and accelerators. You push code or containers; we handle everything from build to global deployment, running workloads in secure, lightweight virtual machines on bare-metal servers around the world.

Before jumping into AI data cleaning directly, let’s first understand data cleaning itself. Data cleaning, also known as data scrubbing, is a critical data preparation step where organizations remove inconsistencies, errors, and anomalies to make datasets ready for analysis. The cleaning process may involve actions like removing null values, correcting formatting, fixing syntax errors, eliminating duplicate data, or merging related fields like City and Postal Code.

Everything you need to know about dbt explained; plus how SQL-based modeling helps teams turn raw data into analytics-ready outputs.

APIs (Application Programming Interfaces) and SDKs (Software Development Kits) are vital components of modern software development. APIs enable applications to communicate and exchange data, while SDKs typically provide a comprehensive toolchain, libraries, and documentation to build features as robust as possible, or even an entire application.

React 19 introduces a suite of features that empower developers to build seamless, performant user interfaces. Among these, async transitions stand out as a game-changer for handling asynchronous operations without freezing the UI. This is particularly impactful when building forms where users expect instant feedback, smooth interactions, and no jarring loading states.

Turn quality into a strategic advantage—accelerate outcomes with Sauce AI.