What Is Kore.ai? Artemis, Pricing and Alternatives (2026)

Kore.ai is an enterprise platform for building, governing and running AI agents across customer service, employee support and back-office work, used by 500+ Global 2000 organizations. Its current generation is the Kore.ai Agent Platform Artemis edition, launched on 21 May 2026 on Microsoft Azure first. There's no public rate card: third-party teardowns cite $500 in free credits, about $0.20 per 15-minute self-service session, and enterprise contracts from roughly $50,000 to $300,000+ a year. It suits large, often regulated enterprises with in-house AI expertise; it's overkill for a team that just wants AI on its help desk. We build an AI support product ourselves and say where it fits near the end; anything we couldn't verify is labeled.

What is Kore.ai?

Kore.ai is an enterprise conversational and agentic AI platform for building, deploying and managing AI agents that handle customer and employee interactions across channels. It positions itself as model-, data-, channel- and cloud-agnostic, with pre-built applications for banking, healthcare, HR, IT and more (kore.ai). In September 2026 its homepage leads with the Artemis tagline "Build. Scale. Optimize." and notes the site is being rebuilt, so you'll see old and new product names side by side for a while.

The company was founded in 2014 by Raj Koneru, still its founder and CEO, a serial entrepreneur whose earlier companies include Kony, iTouchPoint, Seranova and Intelligroup (Kore.ai about). It grew from a chatbot platform into a full agentic-AI suite. For years its umbrella brand was XO, Experience Optimization: improving customer, agent and employee experiences with AI-native products.

Kore.ai frames its portfolio around three "AI for" motions: AI for Service (customer self-service and contact-center automation), AI for Work (employee productivity across IT, HR and knowledge) and AI for Process (agentic automation of back-office workflows). That framing separates Kore.ai from a pure support tool: it's built to sit across the whole enterprise, not just the support inbox.

Kore.ai has reportedly raised about ~$223M in total, including a $150M round led by FTV Capital in January 2024 with participation from NVIDIA and existing investors (Kore.ai news). Its May 2026 press materials describe 500+ Global 2000 organizations as customers; publicly referenced names include PNC Bank, AT&T, Cigna, Coca-Cola, Airbus, Roche, Experian, Deutsche Bank and CVS. The base skews toward regulated, high-volume industries (banking, healthcare, insurance, telecom, retail), which tells you where the platform's design priorities lie.

How does Kore.ai's AI work?

Kore.ai has two layers worth separating: the XO Platform, its mature dialog engine, and the newer Agent Platform, now in its Artemis edition, which handles multi-agent orchestration and governance.

The XO Platform

On the XO Platform, teams build virtual assistants and agents with a no-code/low-code dialog builder, train them with multi-engine NLU for intent recognition, and deploy across channels without rebuilding for each one (Kore.ai for service). The dialog builder gives designers explicit control over flows, entities, context and fallback behavior. Regulated buyers in banking and healthcare want exactly that deterministic control, because a hallucinated answer there is a compliance problem, not just an embarrassment.

XO straddles no-code and pro-code: business teams assemble flows visually, while developers use scripting, custom JavaScript, API service nodes and webhooks for the parts that need engineering. A conversation designer and a software engineer can work on the same assistant without blocking each other, which is a large part of why big organizations pick it.

GALE, the generative-AI layer

To bring the dialog engine into the LLM era, Kore.ai introduced GALE (Generative AI Layer for Enterprises): prompt management, model evaluation and comparison, retrieval-augmented generation over enterprise knowledge, and security/governance controls. It's model-agnostic, so teams can evaluate LLMs side by side and route each task to whichever performs best. GALE bridges Kore.ai's flow-based heritage and the open-ended generative behavior enterprises now expect.

Voice and digital channels

Kore.ai treats voice and digital as equals. The same agent can run on web and mobile chat, WhatsApp and messaging apps, email and real-time voice over telephony and contact-center platforms. It ships a Voice Gateway and integrates with contact-center suites (Genesys and others), so one agent can answer a phone call and a web chat with shared logic. For enterprises whose highest-volume channel is still the phone, that's a real difference from chat-only tools.

What is Artemis, the new Agent Platform?

Kore.ai spent 2025 building toward multi-agent orchestration: specialized agents that hand work to each other instead of one monolithic bot. On 21 May 2026 it launched the Kore.ai Agent Platform Artemis edition, described as an "AI-programmable, AI-native foundation that builds, governs, and optimizes the agents, systems, and workflows running across the enterprise" (Kore.ai announcement). Three pieces matter:

• Agent Blueprint Language (ABL): a compiled, declarative language for defining, validating and governing agents, systems and workflows. Agents become code that can be checked before deployment rather than configuration clicked together in a UI.
• Six built-in orchestration patterns: supervisor, delegation, handoff, fan-out, escalation, and agent-to-agent federation.
• Arch: an AI "agent architect" that turns business objectives into ABL, designs the agent topology and refines agents from production traces.

Artemis launched on Microsoft Azure first, integrated with Azure identity, Microsoft Foundry and Microsoft Agent 365, with other clouds "to follow." Kore.ai also keeps pushing cross-framework agent management: governing agents built in Kore.ai or in LangGraph, CrewAI, AutoGen, Google ADK, AWS AgentCore, Microsoft Foundry and Salesforce Agentforce from one control plane. The bet is that enterprises will build agents in many frameworks and need one neutral governance layer. Artemis is four months old, so validate how mature it is on your cloud and stack before you plan around it.

Vertical and functional apps

Kore.ai also packages pre-built vertical and functional applications that shorten time-to-value:

• BankAssist: banking and financial services (balances, transactions, disputes, card servicing).
• HealthAssist: healthcare (appointments, benefits, member and patient support).
• RetailAssist: retail and ecommerce service (orders, returns, product help).
• IT Assist and HR Assist: employee-facing service-desk automation. The new homepage lists AI for HR, AI for IT and AI for Recruiting.
• SearchAssist / Search AI: enterprise search and knowledge answers grounded in your documents.
• WorkAssist: an employee productivity agent spanning workplace tools.

These are configurable starting points with domain intents, flows and integrations already wired.

Deployment, security and compliance

Kore.ai supports public-cloud SaaS, sovereign/regional cloud, private cloud and on-premises deployment, with data residency by region. Its security and compliance page lists SOC 2 Type II, ISO 27001, PCI DSS, HIPAA (with a BAA), GDPR, HITRUST and FedRAMP Moderate authorization. That depth is one of the clearest reasons a bank, hospital network or government agency shortlists Kore.ai over a SaaS-only tool.

Integrations

The platform ships 100+ purpose-built integrations across contact center (CCaaS), CRM, ITSM and other enterprise systems, plus API/webhook service nodes for anything else, and connects to the major cloud providers.

What are Kore.ai's key features?

• Agent Platform, Artemis edition: ABL, Arch and six orchestration patterns for multi-agent systems (May 2026).
• XO Platform: no-code/low-code and pro-code dialog builder with multi-engine NLU.
• GALE: prompt management, model evaluation, RAG and governance for LLMs.
• AI for Service / Work / Process: customer support, employee assistance and back-office automation.
• Contact-center products: voice and digital AI agents, agent assist, quality management and an AI-native contact center.
• Voice + digital: real-time voice plus web, mobile and messaging from one build.
• Cross-framework agent management (LangGraph, CrewAI, AutoGen, Agentforce and more).
• Vertical/functional apps: BankAssist, HealthAssist, RetailAssist, IT Assist, HR Assist, SearchAssist, WorkAssist.
• Flexible deployment: SaaS, sovereign, private cloud or on-premises with regional data residency.
• Compliance: SOC 2 Type II, ISO 27001, PCI DSS, HIPAA, HITRUST, FedRAMP Moderate.
• 100+ enterprise integrations across CCaaS, CRM and ITSM, plus API/webhook nodes.

How much does Kore.ai cost?

There is no official public rate card. The old kore.ai/pricing URL returned a 404 on 24 September 2026, and serious deployments go through sales and a negotiated contract. Kore.ai's docs describe some usage-based billing mechanics, and third-party teardowns fill in the rest (Featurebase, Quiq, eesel AI, CloudTalk):

• Free credits: new accounts reportedly get $500 in free credits, valid for about 90 days, on a pay-as-you-go Standard workspace. Development and testing are reported as free; charges start when an agent handles live traffic. There's no permanent free plan, and a $100 minimum purchase is reported after the credits run out.
• Automation AI (self-service): billed in 15-minute conversation sessions, at a reported ~$0.20 per session. Cheap per unit, but it adds up at high volume, and long conversations use more sessions.
• Contact Center AI and Agent AI: billed per seat, with third-party estimates of roughly $50–$150 per seat per month.
• Entry deployments: practical small deployments are often reported at $500–$1,500/month once real usage and modules are included.
• Enterprise contracts: negotiated, commonly reported at about $50,000 to $300,000+ per year depending on volume, channels, modules and deployment model. Premium support SLAs can carry their own fee.

What drives the cost. The billing is blended: session-based for self-service, per-seat for agent-facing and voice products, so your total depends on your channel mix, conversation volume and headcount. Cost scales with adoption: more conversations, voice (pricier than chat), longer sessions, more languages and premium modules all push it up. Deployment model matters too: private-cloud, sovereign or on-premises deployments usually cost materially more than SaaS. Session billing also means Kore.ai earns more when conversations run long, so measure how many sessions a typical resolved conversation uses in your pilot.

Treat every dollar figure here as a third-party estimate and confirm your scenario with Kore.ai. None of these estimates yet reflect Artemis-specific pricing, which Kore.ai hasn't published.

What reviewers say: Kore.ai holds 4.6 out of 5 from 507 reviews on G2, checked 21 September 2026, one of the largest review samples of any vendor in this series. That makes the recurring complaints below about implementation effort worth more than a handful of anecdotes.

What are Kore.ai's pros and cons?

Strengths

• Mature enterprise platform. Over a decade of conversational-AI engineering: fine-grained dialog control, strong multi-engine NLU, and broad channel and integration coverage.
• Broad scope. Customer and employee experiences, self-service and agent-facing, chat and real-time voice, from one foundation.
• No-code and pro-code. Business teams and developers build on the same agent.
• Deployment and compliance depth. SaaS, sovereign, private cloud and on-premises, plus SOC 2, ISO 27001, PCI DSS, HIPAA and FedRAMP Moderate.
• Pre-built vertical apps. BankAssist, HealthAssist, RetailAssist and IT/HR Assist give regulated buyers a head start.
• Agent governance. Artemis and cross-framework management target the multi-agent, multi-framework enterprise.
• Customer proof. 500+ Global 2000 customers (named ones include PNC, AT&T, Cigna, Coca-Cola, Deutsche Bank and CVS) reduce vendor-viability risk.
• Free credits to build and test before committing, which is uncommon in this segment.

Limitations

• Steep learning curve. G2 and Gartner Peer Insights reviewers consistently say advanced features are hard to master, and mention occasional bugs in the XO Platform such as sub-intent issues and chatbot crashes (G2). Real value usually needs trained conversation designers.
• Complex pricing. Session, request and per-seat billing across modules make forecasting hard, and with no public rate card every serious buyer negotiates.
• Enterprise-weight implementation. Deployments are sales-led and need internal expertise and often a services engagement.
• Breadth over focus. A team that just wants ticket deflection on an existing help desk pays for configuration surface it will never use.
• Fast platform churn. XO, GALE, the Agent Platform and now Artemis overlap, and the website itself is mid-rebrand. Validate current features rather than relying on last year's docs.

Who is Kore.ai best for, and who should skip it?

Best for: large enterprises, especially in regulated industries like banking, insurance and healthcare, that need a governable conversational and agentic platform across customer and employee experiences, require voice and on-prem or sovereign deployment, have the internal expertise to build on it, and want to manage a growing fleet of agents (including ones built in other frameworks) from one control plane. For that profile, Kore.ai is a legitimate leader.

Not for: SMBs and lean support teams, anyone who wants a fast, self-serve path to AI on an existing help desk, or teams that only need customer-support automation and don't want to build and govern a full platform. For them, Kore.ai's scope is overkill and its learning curve is a tax.

How does Kore.ai compare with alternatives?

Kore.ai sits in a crowded enterprise field. The shortlist:

Where we fit, since we'd rather be upfront than pretend to be neutral. Macha is an AI agent layer that runs on top of your existing help desk (Zendesk, Freshdesk, Gorgias, Front, HubSpot or Intercom), not a broad conversational platform like Kore.ai. We don't match Kore.ai on voice, employee experience or contact-center orchestration; we focus on customer-support automation for teams that already run a help desk. The practical differences: you start on a free trial with $50 of usage instead of a sales-led implementation, setup is done for you (the Macha team analyzes your past tickets, builds the knowledge base and the agent, and runs it in safe mode, with drafts as internal notes, until the drafts are right), and billing is per ticket (about $0.40 a ticket, from $299 a month for 750 tickets, one charge per thread however many messages) rather than a mix of session and per-seat fees. That price covers a dedicated success manager who handles your changes after go-live (new categories, instruction edits, new tools). If you need a governable enterprise platform across customer and employee channels, with voice and on-prem, Kore.ai (or Cognigy or Agentforce) is the right category. If you need AI support on the help desk you already run, that's Macha. See AI agents for customer service and custom tools for how agents take real actions.

Two of those alternatives have full guides here: Cognigy, the closest like-for-like on enterprise conversational AI, and Agentforce, if your system of record is Salesforce and you'd rather activate an agent layer inside it.

How we researched this: Features, pricing and customer figures come from Kore.ai's own pages, its May 2026 Artemis announcement and the third-party sources linked inline. On 24 September 2026 we re-checked the homepage, the pricing URL (404), the customer count, the compliance list and the free-credit terms. The G2 rating and review count were read in a real browser on 21 September 2026, since G2 blocks scripted requests.

Frequently asked questions

What is Kore.ai? Kore.ai is an enterprise conversational and agentic AI platform for building and deploying AI agents across customer and employee channels. Founded in 2014 by Raj Koneru, it built its name on the XO (Experience Optimization) Platform and launched the Artemis edition of its Agent Platform on 21 May 2026 for multi-agent orchestration and governance.

How much does Kore.ai cost? Kore.ai doesn't publish a rate card. Reported billing includes $500 in free credits for new accounts, Automation AI billed in 15-minute sessions at roughly $0.20 per session, Contact Center AI and Agent AI billed per seat (roughly $50–$150/seat/month), and enterprise contracts from about $50,000 to $300,000+ per year. These are third-party estimates; costs scale with volume, channels (voice costs more), modules and deployment model.

What is the XO Platform? XO (Experience Optimization) is Kore.ai's long-standing core platform: a no-code/low-code and pro-code dialog builder with multi-engine NLU and omnichannel deployment, used to build enterprise virtual assistants and agents across chat and voice.

What is GALE? GALE (Generative AI Layer for Enterprises) is Kore.ai's framework for bringing large language models into the platform safely: prompt management, model evaluation and comparison, retrieval-augmented generation over enterprise knowledge, and governance controls. It's model-agnostic.

What is the Kore.ai Agent Platform? It's Kore.ai's foundation for building, governing and optimizing AI agents and workflows across the enterprise. The Artemis edition, launched on 21 May 2026 on Microsoft Azure, adds Agent Blueprint Language (ABL), six orchestration patterns and an AI agent architect called Arch, and it can manage agents built in LangGraph, CrewAI, AutoGen, Salesforce Agentforce and other frameworks.

Does Kore.ai support voice, and can it be deployed on-premises? Yes to both. Kore.ai supports real-time voice over telephony and contact-center platforms alongside chat and messaging, and offers SaaS, sovereign/regional cloud, private cloud and on-premises deployment with regional data residency, backed by SOC 2, ISO 27001, PCI DSS, HIPAA and FedRAMP Moderate compliance.

Who uses Kore.ai? Kore.ai reports 500+ Global 2000 organizations. Publicly referenced customers include PNC Bank, AT&T, Cigna, Coca-Cola, Airbus, Roche, Deutsche Bank, Experian and CVS, concentrated in banking, telecom, healthcare, retail and other large regulated enterprises.

Is Kore.ai good for small businesses? Generally no. It offers free credits for testing, but Kore.ai is an enterprise platform with a steep learning curve, quote-only pricing and sales-led implementation. Smaller teams are usually better served by self-serve tools that layer onto an existing help desk.

What are the main alternatives to Kore.ai? Salesforce Agentforce and Cognigy are close enterprise peers (voice + chat, sales-led). For customer-support automation specifically, Intercom Fin publishes per-outcome pricing, and Macha is an AI agent layer on top of an existing help desk that the Macha team sets up and runs for you, at about $0.40 a ticket including a dedicated success manager.

Should Kore.ai be on your shortlist?

Put Kore.ai on the list if you're a large enterprise, especially in a regulated industry, that needs one governable platform across customer and employee channels, with voice and flexible deployment, and has the people to build on it. Artemis makes it a serious option for teams already running agents in several frameworks, provided you're on Azure or can wait for other clouds.

Leave it off if you need predictable costs from day one or a fast path to AI on a help desk you already run. The blended session and seat pricing is hard to forecast, the implementation is enterprise-weight, and a lighter AI layer will cover most support automation with far less overhead.

Checked 24 September 2026 against Kore.ai's site, its Artemis announcement, its security and compliance page, G2 and independent pricing teardowns. All prices are third-party estimates; confirm with Kore.ai.