Juhi Tiwari
Juhi is a Research Lead at Kore.ai, driving market intelligence, competitive insights, and analyst-facing strategy that strengthens the company’s industry positioning. She also works as a content strategist, creating deep technical content that translates complex AI concepts into clear, compelling narratives. Her work supports Kore.ai’s vision, credibility, and thought leadership across the AI landscape.
Articles by this author
Voice AI agents in healthcare: Top use-cases
Voice AI agents are helping healthcare organizations automate administrative interactions while keeping clinical decisions with healthcare professionals. This article explores healthcare voice AI use cases including appointment scheduling, insurance verification, prescription support, billing, referrals, post-discharge follow-ups, and multilingual patient service. It also highlights Kore.ai voice AI deployments and addresses PHI protection, compliance, auditability, testing, and secure integration with healthcare systems.
Voice AI agents in banking: Top use-cases
Voice AI agents are helping banks automate customer service while supporting secure, personalized interactions. This article explores banking voice AI use cases including transaction inquiries, card reporting, fraud alerts, payments, loan updates, collections, and multilingual service. It explains how Kore.ai integrates voice AI with banking systems while applying identity verification, security controls, policy enforcement, auditability, and human escalation for complex or sensitive requests.
Why AI agents need an Agent Development Lifecycle (ADLC) to deliver real ROI
The Agent Development Lifecycle (ADLC) provides a structured framework for building, validating, deploying, governing, and continuously improving enterprise AI agents. This article explains how teams move from business requirements to production through architecture, testing, deployment, observability, evaluation, and optimization. Kore.ai Artemis supports the lifecycle with agent governance, evaluation, observability, and controlled deployment, helping enterprises build reliable, measurable, and production-ready agentic AI systems.
Introducing Dual-brain architecture: Reasoning and control, together
Dual-Brain Architecture combines flexible AI reasoning with deterministic enterprise controls. Kore.ai Artemis uses an Agentic Brain to interpret requests, reason across context, and determine actions, while a Deterministic Brain enforces business rules, policies, permissions, and predictable workflows. A Shared Spine maintains context between both layers. This architecture enables enterprise AI agents to handle complex interactions while maintaining governance, control, and auditability.
Human capital and token capital: why enterprise AI value depends on both
Enterprise AI value comes from combining human capital with token capital, including AI agents, models, systems, and workflows. This article explores how human judgment, institutional knowledge, and relationships can work alongside AI agents through human-in-the-loop processes. It also covers AI agent governance, observability, auditability, and policy enforcement. Kore.ai Artemis provides controls that help enterprises scale agentic AI while preserving human oversight.
How to build AI Agents with Arch AI - Kore.ai's build-in AI Architect
Arch AI is Kore.ai’s built-in AI architect for designing, building, testing, deploying, and optimizing enterprise AI agents. The article explains how Arch AI supports the Agent Development Lifecycle, transforming business requirements into agent architectures and Agent Blueprint Language (ABL) artifacts. It incorporates evaluation, governance, observability, runtime traces, and optimization, helping enterprises create production-ready AI agents with greater consistency, traceability, and control.