Our goal has always been to fix QA. With today’s release, we’re closer than anyone else to doing it. Tests in Rainforest now fix themselves, creating more reliable results while allowing your team to focus on what matters — shipping code. Everyone has to do QA, but everyone hates doing QA. That’s why we started Rainforest in 2012. We make tools that make QA suck less.

Learn about our reimagined version of Kwo Ding's original mobile test automation pyramid for modern DevOps practices.

Customer care organizations are facing the disruptions of an AI-enabled future, and gen AI is already impacting customer care organizations across use cases like agent co-pilots, summarizing calls and deriving insights, creating chatbots and more. In this blog post, we dive deep into these use cases and their business and operational impact. Then we show a demo of a call center app based on gen AI that you can follow along.

Data completeness plays a pivotal role in the accuracy and reliability of insights derived from data, that ultimately guide strategic decision-making. This term encompasses having all the data, ensuring access to the right data in its entirety, to avoid biased or misinformed choices. Even a single missing or inaccurate data point can skew results, leading to misguided conclusions, potentially leading to losses or missed opportunities.

It was lovely to see so many of the community and hear about the latest data streaming initiatives at Kafka Summit this year. We always try to distill the sea of content from the industry’s premier event into a digestible blog post. This time we’ll do it slightly differently and summarize some broader learnings, not only from the sessions we saw, but the conversations we had across the two days.

Have you ever wondered what it feels like to manually label thousands of images for your project? You know the drill: endless hours looking at screens, second-guessing every tag, and facing the fear of mistakes that could throw off your entire analysis. It's a real headache. You spend more time guessing than making progress, whether trying to align your team's vision or ensuring every detail matches the client's expectations. Here's where image annotation tools step in.

When building your Laravel applications, you may sometimes need to use a NoSQL database to store and retrieve data. One popular choice is Amazon DynamoDB, a fully managed, serverless, and highly scalable NoSQL database service provided by Amazon Web Services (AWS). In this article, we'll take a brief look at DynamoDB. We'll then delve into how to use DynamoDB as a cache store in Laravel, and how to store Laravel models in DynamoDB using the baopham/laravel-dynamodb package.

Working with large volumes of data requires effective data management practices and tools, and two of the frequently used processes are data ingestion and ETL. Given the similarities between these two processes, non-technical people seek to understand what makes them different, often using search queries like “data ingestion vs ETL”.

If you have a legacy system with customized capabilities and valuable features but nearing end of life, refactoring the system is a potential choice for modernization. Insurance platform modernization usually involves one-to-one code migration, which can often be more costly and time consuming than expected and typically tends to miss some of the integration and data architecture modernization that is foundational for getting the full value of digitization.

We tested a product-led go-to-market motion last year. Here are the exciting results and learnings.