Gaurav Bhandari
Gaurav is the Content Lead at Kore.ai. He has over 10 years of experience creating content and designing marketing campaigns that drive organic growth for B2B companies. As both an engineer and a marketer, he excels at translating technical concepts into compelling marketing content. Outside of work, he enjoys long walks and playing badminton with his 10-year-old daughter.
Articles by this author
How to build AI agents from scratch in 2026 (no coding required)
Building an AI agent is easy, but making it enterprise ready is not. Production agents need real system access, governance, and observability, not just a working prototype. There are four ways to build one: custom code, open source frameworks, cloud services, or an enterprise agent platform, but only platforms give you the full production stack out of the box. Getting the agent built is step one. What determines success is how well you monitor, govern, and improve it afterward.
AI agent fragmentation trap: Why AI agents speed up teams but slow down enterprises
Enterprises deploying AI agents team by team are repeating the shadow IT problem, only at a bigger scale. Without shared orchestration, agents fragment across four areas: context, governance, identity, and workflow coordination, leading to conflicting outputs and slower decisions. The real cost is decision debt and compliance risk. The fix is a unifying layer that gives agents shared context, consistent governance, clear identity, and coordinated workflows across teams.
Build vs buy AI agents: How enterprises get stuck building the wrong layer
AI coding tools make it easy to build an agent fast, but building the infrastructure around it, orchestration, guardrails, state handling, observability, is where teams get stuck. That layer looks the same across every enterprise and becomes fragile and hard to maintain over time. The real build vs buy answer is to buy the infrastructure layer from a platform and build the part only your engineers can define, such as your use cases, workflows, policies, and business logic.
AI agents for HR: 10 proven use cases & examples (2026)
AI agents for HR are software agents that complete HR workflows end to end. They read requests, pull data from HR systems, apply policy, take action, and hand sensitive cases to people. The strongest use cases today are onboarding, the HR helpdesk, leave, payroll queries, and policy compliance.
8 best AI agent and agentic AI platforms for retail & ecommerce | 2026 market guide
This guide reviews the 8 best agentic AI platforms for retail and ecommerce in 2026: Kore.ai, Sierra AI, Gorgias, Algolia, Clerk.io, Decagon, Insider One, and ViSenze. Not all agentic AI platforms are equal. Real value needs context awareness, multi step reasoning, action in backend systems, and improvement over time. Integration depth with your commerce, OMS, and CRM systems matters more than flashy AI. Match the platform to your actual need.
Top 10 agentic AI platforms for banking & finance (2026)
This guide reviews the top agentic AI platforms for banking and finance in 2026: Kore.ai, Boost.ai, ServiceNow, Kasisto, Posh AI, Salesforce, Glia, and Interface.ai. Most banks are already using agentic AI with strong results. The real differentiator is readiness, meaning how much custom engineering and compliance work stand between you and a live banking workflow. Look for a platform built for financial services from the ground up, with pre-built banking agents, native integrations, and governance already in place.