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.

Snowflake and Salesforce are happy to share that bidirectional data sharing between Snowflake, the Data Cloud company and Salesforce Data Cloud is now generally available. In September, we proudly announced that organizations could begin leveraging Salesforce data directly in Snowflake via zero-ETL data sharing to unify their customer and business data, accelerate decision-making and help streamline business processes.

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

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.

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.

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.

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.

What is hyperautomation for insurance? It might sound like just another buzzword, but let’s peel back the layers to see how hyperautomation works. Imagine this: you go on a deep dive to evaluate your insurance company’s processes and operational models. You discover inefficiencies, lag times, and that your team manages transactions with disparate, often manual processes. It’s clear you need a new solution. And the solution you need doesn’t currently exist.

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.

New legislation affirms the governance and security responsibilities of all organizations doing business in the EU.