AI is advancing quickly. But trust still lags. On April 7 at 11:30 AM EST, Cobus Greyling hosts AI Activations with Soo-Jin Lee to unpack what it takes to design AI people can actually trust. We will cover: • Why AI feels smart but not intuitive • Balancing brand voice with real user behavior • Designing for edge cases and failure paths Save your spot: https://lnkd.in/gsBW5gJm
Kore.ai
Technology, Information and Internet
Orlando, Florida 101,505 followers
Kore.ai drives AI value with tools for work, process, and service—powered by an agent platform and no-code solutions
About us
Kore.ai, a leader in enterprise AI, accelerates business outcomes from AI with agentic AI applications built on the industry-leading Kore.ai Agent Platform. Its growing catalogue includes pre-built solutions for banking, healthcare, and retail; horizontal applications for IT, HR, and recruiting; and marketplace that help enterprises deploy AI agents quickly across additional industries and use cases. Open and agnostic by design, Kore.ai gives organizations flexibility in choosing AI models, cloud infrastructure, and enterprise systems. Trusted by nearly 500 Global 2000 companies, Kore.ai enables secure, scalable AI adoption worldwide. With its roots grounded in the Enterprise, Kore.ai brings years of experience in AI applications for customer service, workplace productivity and process automation. The company has a strong patent portfolio in the AI space and has been recognized as a leader and an innovator by top analysts. Headquartered in Orlando, Kore.ai has a network of offices to support customers in India, the UK, the Middle East, Japan, South Korea, and Europe. Visit Kore.ai to learn more.
- Website
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https://kore.ai
External link for Kore.ai
- Industry
- Technology, Information and Internet
- Company size
- 501-1,000 employees
- Headquarters
- Orlando, Florida
- Type
- Privately Held
- Founded
- 2013
- Specialties
- Generative AI, Conversational AI, Artificial Intelligence, Enterprise AI, NLP, Natural Language Processing, Large Language Model, Customer Experience, User Experience, Employee Experience, Agent Experience, Search Experience, App Experience, and Agentic AI
Products
Locations
Employees at Kore.ai
Updates
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Out-of-the-box topic models look impressive until they hit real-world data. Labels drift. Context gets lost. And teams end up doing the work AI was supposed to eliminate. The issue isn’t modeling. It’s alignment. In this session, Prakash Anto walks through how a taxonomy-led approach to Topic Discovery changes that, anchoring AI to how your business actually thinks: products, intents, contact reasons. From there, every conversation is mapped with clarity, surfacing sentiment, resolution, and volume trends in near real time. See how that shift plays out in practice: https://lnkd.in/gPKRJwQz
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Getting agents live was never the hard part. Managing them effectively is. At HumanX 2026, Cathal McCarthy (CSO, Kore.ai) is hosting a Peer Xchange roundtable: Managing Your Agent Workforce A room of leaders digging into what actually happens after deployment because this is where things get real. The harder questions start showing up: Who’s accountable? Is governance helping or slowing you down? Are your agents actually driving outcomes? If you’re past the pilot stage, this is a conversation worth being in. Register here - https://lnkd.in/gNB2Fs7E
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Designing AI that works is one thing, but designing AI that people can actually trust and engage with is another. On April 7 at 11:30 AM EST, join Soo-Jin Lee behind conversational experiences at Amazon, Google, Netflix, and Wells Fargo for a closer look at what it takes to bridge that gap. If your AI is something people actually use, this session is worth your time. Register here: https://lnkd.in/gsBW5gJm
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Most voice AI sounds good but very little of it works when things actually get complex. Rescheduling an appointment is simple. Resolving a billing dispute across systems, policies, and handoffs? That’s where things break. Because at that point, it’s no longer about speech. It’s about orchestrating context, decisions, and workflows in real time. The enterprises getting this right aren’t locked into one approach. They’re building on platforms flexible enough to adapt without rebuilding the stack every time. That’s what enables reliability at scale. We break this down in our latest AI Pulse session - https://lnkd.in/gBtGRQ3e
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AI in healthcare sounds great in theory. But what does it look like in practice? At HIMSS 2026, we unpacked how teams are improving access, cutting admin work, and moving from pilots to real-world use. If you missed it, its now available on demand. Gary Fingerhut (Kore.ai) and Michael Duke (Guidehouse) break it down in 20 mins. Watch here: https://lnkd.in/gp9C-U6U
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Everyone is building AI. But few are closing the loop. From a single intent through reasoning, context retrieval, tool orchestration, to full workflow completion. That’s where orchestration becomes the product. And trust becomes the constraint. Some domains are ready. Some don’t hold under real-world conditions.
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Invoice fraud isn’t a new problem. But the way it’s evolving is. It’s no longer just about fake invoices. It’s near-perfect replicas, small changes in payment details, and issues that slip past even careful checks. And the reality? Most finance teams are still relying on manual verification to catch it. Which, over time, just doesn’t scale. In this piece, Sreeni Unnamatla explains how agentic AI turns reactive checks into continuous, context-aware validation. https://lnkd.in/e___hAia
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If your AI stack is growing but outcomes aren’t really compounding, there’s a good chance you’re actually scaling the wrong layer. We’re seeing a consistent pattern: teams are building more agents, more copilots, more automation but the underlying search layer remains fragmented and that’s exactly where things break. In a recent conversation between Uma Sandilya and Rowan Curran, one point stood out: most AI problems are actually search problems underneath. This piece gets into the layer most teams overlook: search and retrieval, the foundation that actually determines whether AI can actually reason, decide, and act with confidence. Because when context is weak, everything built on top of it becomes unreliable. https://lnkd.in/gAKY8x2u
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Nice to see Kore.ai on the curve, alongside the platforms moving agentic AI from idea to execution 🙌🚀 Right where the shift is actually happening💪
Everest Group’s Agentic AI Products PEAK Matrix® Assessment 2026 evaluates 27 leading providers, benchmarking them on vision, technology architecture, orchestration maturity, governance mechanisms, and market impact. Amazon Web Services (AWS) Ema Google IBM Kore.ai Microsoft Salesforce Appian Automation Anywhere Avaamo Druid AI EvoluteIQ HCLSoftware Leena AI Lyzr AI n8n Neutrinos OneReach.ai. ServiceNow SoundHound AI Tungsten Automation UiPath WRITER Laiye Newo.ai. Zvolv The report explores: 🔹 How agentic AI systems combine LLMs, SLMs, memory layers, orchestration frameworks, and enterprise tool integrations 🔹 Key technology innovations enabling adaptive, goal-directed execution models 🔹 The evolving provider landscape for prebuilt agents and agent builder platforms 🔹 Practical considerations for enterprises evaluating agentic AI solutions Read on: https://okt.to/Jmxa20 Get in touch: Anil Vijayan Vaibhav Bansal Vershita Srivastava Yusuf Ahsan Niveditha Arjun Upshant Saini Pragya Sultania #AgenticAI #ArtificialIntelligence #EnterpriseAI #Automation #DigitalTransformation #PeakMatrix
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