A customer who gets instant, hyper-relevant recommendations from Netflix expects the same from their bank. A shopper who receives proactive delivery updates from Amazon expects the same from every brand they interact with. This is the new baseline: personalization is no longer a differentiator, it’s an expectation. According to McKinsey research, 76% of customers expect […]
2026
Auto Recommendation Algorithm Selector: How LLMs Are Redefining the Way We Choose ML Algorithms
Building a recommendation system is hard. Not just the engineering, but the decision-making process before you write a single line of model code. Will you use collaborative filtering? Will you have sufficient user behavior signals to apply a deep learning approach? What if you’re launching a new product with zero data, a classic cold start […]
Reduce Cart Abandonment With AI Agents at Scale
Cart abandonment is one of the biggest challenges for ecommerce businesses today. Products added to the cart are dropped off at the last moment. Reasons may vary, from price hesitation to doubts about product details, or anything else. However, at scale, even a small amount of cart abandonment can result in a significant revenue loss. […]
Deep Dive: WhatsApp Integration with Meta (Production Architecture)
Most WhatsApp integration guides stop at “send your first message.” That’s the easy part. The real challenge begins when you try to run it in production, wherein tokens expire, webhooks retry, assets change, and external systems evolve without warning. What looks like a simple API integration is actually a distributed system built on OAuth, event […]
How to Handle Multiple Concurrent User Requests with vLLM
Moving a Large Language Model from a local testing environment to a live, public-facing application poses a significant engineering challenge. The biggest hurdle is serving multiple user requests at the exact same time without destroying response speed or running out of graphics processing unit memory. When many users interact with a model simultaneously, traditional systems […]
AI-Powered Product Recommendation: How AI Agents Guide Customer Decisions
People now use digital commerce for product discovery and purchasing. Customers used to spend time examining extensive product catalogs while they compared different choices and analyzed multiple product reviews before they reached their final decision. Intelligent systems currently handle most of the work that previously required people to complete. AI systems increasingly assist customers in […]
The Rise of AI Agents for Customer Support: Why Businesses Are Making the Shift
Customer support has quietly become one of the most complex operational functions inside modern businesses. The reason is simple: customer expectations have changed faster than support infrastructure has. A decade ago, customers were fine with waiting for long hours, sometimes even days, to solve issues. However, today, the reality is completely different. Customers expect immediate […]
Instagram AI Agent: How to Automate Customer Service and DMs with Exei
Instagram is no longer just a social media platform. For D2C and e-commerce brands, it has evolved into a full-scale commerce engine. From product discovery through Reels to checkout via DMs, the entire customer journey can now happen inside Instagram. But as Instagram turns into a revenue channel, it also becomes an operational challenge. Hundreds […]
How AI Agents Improve First-Contact Resolution at Scale?
Solving customers’ queries on the first call is not a cherry on top, but it’s a necessity for customer support. Customers like their issues ot be solved immediately, without waiting too long on hold, call redirecting from one to another, and daily follow-ups. Brands having an online presence need their support team to always be […]
Voice AI Agent: Eliminate Operational Bottlenecks at Scale
How Voice AI Agents Reduce Operational Bottlenecks Operational bottlenecks rarely begin as dramatic failures. They start as small inefficiencies – rising call volumes, longer resolution times, fragmented workflows, staffing gaps, repetitive escalations. Over time, these friction points compound into revenue leakage, declining customer experience, and stressed teams. For industry leaders, the real question is not […]










