Operations | Monitoring | ITSM | DevOps | Cloud

When it comes to keeping your business’s lights on, you need to manage and orchestrate your operational activities, prioritize high-impact and urgent work, and maintain day-to-day precision. Trust is paramount during mission-critical, time-sensitive crisis response and the narrow margin for error means there is little room and low acceptance for generative AI hallucinations or false positives.

The retail industry is going through a period of major upheaval. AI is transforming the landscape at a rapid pace. Grand View Research evaluated the market value at USD 5.79 billion in 2021 and this is expected to grow at a 23.9% compound annual growth rate (CAGR) from 2022 to 2030. For retailers, this translates into a need to adapt to an entirely new paradigm of customer expectations.

Following our well-received presentations with Walgreens’ Andy Kettlewell at this year’s NRF and RILA LINK shows, we were fortunate to present another testimonial breakout session—this time from a CPG perspective—at Gartner’s annual Supply Chain Symposium/Xpo in Orlando. One of the things I’m especially proud of since the beginning of antuit.ai is the number of customers who’ve been eager to come forward and share their positive experiences with us.

In a previous blog post, we built a small Python application that queries Elasticsearch using a mix of vector search and BM25 to help find the most relevant results in a proprietary data set. The top hit is then passed to OpenAI, which answers the question for us. In this blog, we will instrument a Python application that uses OpenAI and analyze its performance, as well as the cost to run the application.

At Traceloop, we’re solving the single thing engineers hate most: writing tests for their code. More specifically, writing tests for complex systems with lots of side effects, such as this imaginary one, which is still a lot simpler than most architectures I’ve seen: As you can see, when an API call is made to a service, there are a lot of things happening asynchronously in the backend; some are even conditional.

Generative Artificial Intelligence (AI) is commanding conversations these days, a never-before-seen system that’s captured many millions of users since its debut in November 2022. A machine learning innovation that creates content of all kinds (and that’s just the beginning), generative AI also comes up with new product designs and optimizes business processes. We have only begun to exploit and understand this disruption.