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
Your enterprise AI agents don’t lose memory. They drift.
AI agents do not lose memory, they compress it, and that slowly blurs earlier instructions until decisions stop matching the original rules. This shows up as temporal drift on outdated rules, semantic drift on softened meaning, behavioral drift on unintended habits, and coordination drift across multiple agents. Bigger models or larger context windows do not fix this, since drift is an architecture problem. The fix is a durable external source of truth agents can check, not memory alone.
Top 7 agentic AI platforms for healthcare | 2026 market guide
This guide reviews the top 7 agentic AI platforms for healthcare in 2026: Kore.ai, Oracle Health, Avaamo, Salesforce, ServiceNow, Sierra AI, and Hyro. Healthcare enterprises are deploying AI agents across clinical, operational, and patient facing workflows to ease administrative burden. Look for a platform with pre-built healthcare agents, deep EHR integration, and HIPAA compliant governance.
12 best AI workflow automation tools | 2026 market guide
This guide reviews 12 top AI workflow automation tools for 2026 across HR, IT, employee productivity, and customer support: Kore.ai, Moveworks, Automation Anywhere, ServiceNow, UiPath, Glean, Microsoft, Zendesk, and NiCE Cognigy. Most platforms specialize in one function, but Kore.ai is the only one here covering all four areas end to end.
Multi-agent systems fault line: Why enterprise AI systems fail and how to avoid
More agents does not mean better outcomes. Poorly structured multi agent systems can amplify errors up to 17 times and cost over 500,000 dollars a year in extra tokens. The overhead is worth it only when a workflow crosses system boundaries, needs separate expertise or compliance handling, or requires context dependent routing.
8 best AI agents for customer service in 2026
This guide reviews the 8 best AI agents for customer service in 2026: Kore.ai, Zendesk, NiCE Cognigy, Omilia, SoundHound, Sierra AI, Sprinklr, and Yellow.ai. Not all platforms are built the same, some focus on voice or contact centers, others support full multi-agent orchestration. Governance, integrations, and proven scale matter most for enterprise deployment.
AI agents in retail: 12 proven use cases & examples (2026)
88% of retailers use AI, but only 39% see real impact on the bottom line. The gap exists because most AI tools suggest actions instead of executing them. AI agents close it by owning workflows end to end, across product search, personalization, returns, inventory, demand forecasting, dynamic pricing, workforce scheduling, fraud detection, vendor documents, procurement, and performance monitoring.