Organizations can face two critical challenges with conversational AI. First, users need answers where they work—in their CRM, support console, or analytics portal—not in separate tools. Second, implementing a secure embedded chat in their applications can require weeks of development to build authentication, token...
Organizations face challenges in quickly detecting and responding to user account security events, such as repeated login attempts from unusual locations. Although security data exists across multiple applications, manually correlating information and making corrective actions often delays effective response. With Amazon Quick Suite and...
This post was co-written with Davesh Maheshwari from Lendi Group and Samuel Casey from Mantel Group.
Most Australians don’t know whether their home loan is still competitive. Rates shift, property values move, personal circumstances change—yet for the average homeowner, staying informed of these changes is...
In this first post in a two-part series, we examine how retailers can implement a virtual try-on to improve customer experience. In part 2, we will further explore real-world applications and benefits of this innovative technology.
Every fourth piece of clothing bought online is returned...
Large language models (LLMs) perform well on general tasks but struggle with specialized work that requires understanding proprietary data, internal processes, and industry-specific terminology. Supervised fine-tuning (SFT) adapts LLMs to these organizational contexts. SFT can be implemented through two distinct methodologies: Parameter-Efficient Fine-Tuning (PEFT),...
Are you struggling to balance generative AI safety with accuracy, performance, and costs? Many organizations face this challenge when deploying generative AI applications to production. A guardrail that’s too strict blocks legitimate user requests, which frustrates customers. One that’s too lenient exposes your application...
