Systems | Development | Analytics | API | Testing

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How to Implement Gen AI in Highly Regulated Environments: Financial Services and Telecommunications and More

If 2023 was the year of gen experimentation, 2024 is the year of gen AI implementation. As companies embark on their implementation journey, they need to deal with a host of challenges, like performance, GPU efficiency and LLM risks. These challenges are exacerbated in highly-regulated industries, such as financial services and telecommunication, adding further implementation complexities. Below, we discuss these challenges and present some best practices and solutions to take into consideration.

15+ Mobile App Testing Statistics

As global app downloads have doubled every quarter since 2015, and users now spend more time on apps than websites, the need for thorough mobile app testing is more critical than ever. The app testing market is projected to reach $13.6 billion by 2026. This blog will cover key mobile app testing statistics and explore why it is essential for delivering high-quality user experiences and maintaining competitive advantage.

How to Monetize AI APIs: Choosing The Right Metric

Regarding charging for API usage, we usually gravitate towards charging per API call. While this can work for many use cases, it’s not optimal for everyone. This is where choosing the right metric to bill upon and finding a platform that supports it is crucial. In this blog, we will talk about choosing the right metric to bill upon and how to implement it in Moesif. Let’s begin by digging into what a billing metric is and how to decide which one is best to use with your AI APIs and services.

Reverse Tron and the Art of Bringing Code to Life

Ever wondered what it's like to have a virtual robot in your toolkit, a trojan horse in your test scripts, or a lil' rockstar named Selenium? Welcome to the world of test automation, as unfolded by none other than Jason Huggins. In this part 2 episode of our interview with Jason, we continue to dive into the world of testing. You’ll learn how Java and Python enthusiasts have propelled Selenium to global fame with impressive stats and precision, and Jason also sheds light on the power of community.

Dealing with MySQL Lock Timeouts: Bail faster

When using MySQL and InnoDB you will inevitably run into lock timeouts sometime, somewhere. We have recently started seeing this with some of our Shopware 6 customers in their storefronts or worker queues, so I was reminded to go back to 2017 in our codebase when we put a fix in place. In our case, this happened on tables that were constantly written to from many different sources in the code base.

The Bank of Things (BoT): What IoT Brings to Fintech Software Development

IoT is driving the digital metamorphosis in the banking industry. The surge in internet-enabled devices, like smartphones, tablets, and smartwatches, signifies an increase in opportunities for fintech software development to scale their business through the Bank of Things (BoT). IoT technologies are enabling real-time connections, making banking more efficient and customer-centric.

10 Best APIs for Machine Learning

Machine learning APIs provide developers with powerful tools to integrate complex algorithms and models into applications without building them from scratch. These APIs simplify the development process by offering pre-trained models and standardized methods for different tasks. These include image recognition, natural language processing, and predictive analytics. This accessibility democratizes machine learning so that developers of varying expertise can leverage cutting-edge technology efficiently.

Data Actionability: Cost Governance with Unravel's New FinOps AI Agent

80% of data management professionals surveyed cited difficulty accurately forecasting data-related cloud costs (Forrester). Why? They lack granular visibility to allocate costs, the information they need is in silos, and they don’t have AI or automation to forecast spending. With this in mind, Unravel introduces the new FinOps AI Agent. Learn how this new AI agent enables teams to go beyond observing overall spend to taking immediate action with purpose-built AI and automation.

How Generative AI is Transforming Product Engineering?

‍McKinsey’s latest research projects that generative AI could contribute between $2.6 trillion and $4.4 trillion annually across various sectors. Experts have also observed that integrating AI-driven automation, threat detection, and low-code platforms redefines next-gen software development. Whether it is code generation, bug fixing, or even designing a new digital component, generative AI is seeping into all product engineering processes.