As enterprises rapidly embrace AI Agents and Voice AI Agents, one question that consistently arises during customer evaluations, boardroom discussions, and compliance reviews is "Where is the human in the loop?" It’s a fair question. Human oversight has become a cornerstone of trustworthy AI, reinforced by emerging regulations, governance frameworks, and growing expectations around accountability. But there is a practical challenge that organizations rarely discuss. Imagine an enterprise AI Voice Agent handling hundreds of thousands of customer conversations every day. Each interaction…
Voice has rapidly become the main interface between enterprises and their customers. AI voice agents now handle service requests, authentication, payments, and issue resolution at scale. In doing so, they move beyond responding, they actively listen, in real-time and at scale. When AI listens, the security and privacy stakes fundamentally change. The focus is no longer limited to protecting databases and dashboards, but extends to safeguarding live conversations, emotions, and intent. This shift requires enterprises to rethink traditional security and privacy approaches. In this blog, we…
Multi-cloud sounds great on slides. No vendor lock-in Best-of-breed services Higher availability Better negotiation power We believed all of that too At Haptik, we did not set out to build a multi-cloud platform. But over time, we found ourselves running real production workloads across AWS, Azure, and GCP. Not experiments. Not proof of concepts. Customer-facing systems that had to work every day. This is the honest truth about what multi-cloud really gives you, and what it quietly takes away. ALSO READ: Scaling HAProxy on AKS for Billions of Transactions with Dynamic Autoscaling and Token…
In 2025, organizations are moving beyond single-cloud strategies. Running containerized apps on Azure Kubernetes Service(AKS) while tapping into Google’s Vertex AIfor cutting-edge LLMs and generative AI is becoming the new norm.
At our scale, we needed to handle billions of transactions efficiently - routing across multiple environments and internal data centers - while maintaining reliability, security, and dynamic control. To achieve this, we chose HAProxy, a proven, high-performance load balancer known for its lightweight footprint, flexibility, and ability to handle massive concurrency with minimal overhead. This blog walks you through how we deployed HAProxy in high-availability (HA) mode on Azure Kubernetes Service (AKS) -complete with autoscaling powered by KEDA, seamless integration with Azure Application…
Migrating terabytes of live MongoDB data across cloud providers is notoriously difficult. Standard approaches like extending replica sets across clouds fail at scale where initial syncs take weeks, oplogs roll over, and you're stuck in an endless retry loop.
In today’s dynamic enterprise landscape, Customer Experience (CX) is no longer just a service function, it is a strategic advantage. Enterprises are seeking innovative ways to engage customers, personalize interactions, and create seamless, scalable journeys.
We live in a world where communicating or talking to machines has become super normal. You ask your phone for the weather forecast, chat with a bot to know your food delivery status or even command Alexa to play one of your favorite songs — and boom, it just works.
Let’s face it: in the world of microservices, managing traffic and scaling workloads can feel like trying to catch a runaway train. You’re flying down the tracks at full speed, but if you’re not careful, things can get out of hand real quick. We’ve all been there — constantly battling the scale-up and scale-down conundrum, trying to keep the system efficient without wasting resources.
Introduction Large Language Models (LLMs) are advanced AI models trained on vast datasets to perform a wide range of natural language processing tasks. Their widespread adoption in various applications, from chatbots to intelligent decision-making systems, requires a robust security framework to ensure that they function as intended without being susceptible to attacks or misuse. While there are numerous challenges, this blog focuses more on the key issues such as hallucination, ethical use of AI, and data security, and the best ways to address them.
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