Kore.ai
AI ChatUpdated November 11, 2026
Enterprise agentic AI platform for building, governing and improving voice and chat AI agents for customer service, HR, IT and business processes.
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What is Kore.ai?
Kore.ai is an enterprise platform for building, running and governing AI agents that talk to customers and employees over voice, chat and messaging. Its current generation, the Kore.ai Agent Platform Artemis edition, launched in May 2026: agents are defined in a typed language called ABL, drafted by a built-in AI architect called Arch, and executed by one runtime that logs every reasoning step, tool call and handoff. Three packaged product lines sit on top: AI for Service for contact centers, AI for Work for enterprise search, HR and IT, and AI for Process for long-running workflows. The problem it targets is moving agents from pilot to regulated production without losing control. The weak spot is access: there is no self-serve plan, sign-up is limited to approved company domains, and reviewers report a steep learning curve. Pick it if you run a large, compliance-heavy operation with an integration team.
How to start using Kore.ai?
Access starts with sales rather than a sign-up form. The official quick start guide says the Agent Platform is available to Kore.ai customers and partners and that sign-up is enabled only for approved domains, so you request access through Contact us or Get demo on kore.ai. A lower-commitment route is Proof Concierge: you describe a use case, approve a short brief, and Kore.ai builds a working proof-of-concept agent on Artemis for free, which the company says can arrive in as little as one week.
Once your domain is approved, sign in at the regional URL (agents.kore.ai for US-Central, with separate hosts for the UK, Germany, Japan, Australia, Singapore, the UAE, Saudi Arabia and India) and create a workspace. Invite colleagues through the Admin gear icon and Invite members, then open Settings > AI Configuration to register credentials for at least one LLM provider and choose the model Arch will use. The platform does not bundle its own model, so expect to bring keys for OpenAI, Anthropic, Azure OpenAI, Google, AWS Bedrock or another supported provider.
On the Projects page, select Start with Arch. Arch works in three phases. In Interview you describe the agent in plain language or upload an SOP, and Arch asks follow-up questions about channels, integrations and escalation rules. In Blueprint it proposes agents, workflows and integrations that you accept or send back for changes. In Build it generates agents, workflows, tools, prompts and knowledge configuration and opens the project in Studio. Developers can run the same process from an IDE through the MCP server or from the terminal with the CLI.
Before anything goes live, Arch generates an evaluation suite and simulates conversations with synthetic personas, so you see where the agent breaks before a customer does. Replace any placeholder tools with real integrations, rerun the evals, and apply suggested fixes with Auto Tune. Publishing happens in the Deployments workspace: click New Deploy, start in Development, Promote through Staging to Production, and bind a channel such as Web SDK, WhatsApp, Microsoft Teams or a voice line.
Who is it for?
Contact center leaders
By Kore.ai’s count, two thirds of support volume is still voice, and legacy IVR menus frustrate callers. AI for Service combines voice and digital AI agents, real-time agent assist, automated quality scoring and a full contact center suite with workforce management. Automation and human agents end up on one stack with one set of metrics.
HR and IT service owners
Employees wait in ticket queues for simple answers about leave, benefits or access requests. AI for Work responds in Slack, Teams or by voice, files requests and searches company systems through 100+ prebuilt connectors with permission filtering. Your helpdesk keeps only the sensitive and escalated cases.
Regulated enterprises
Banks, insurers and healthcare providers must prove what an agent did and why. Kore.ai enforces policies outside the LLM, traces every agent action and lists SOC 2 Type II, ISO 27001, PCI DSS and FedRAMP Moderate credentials, with deployment from public cloud to on-premises. That shortens the security review instead of stalling it.
Microsoft-centric IT teams
Artemis launched on Azure and integrates with Microsoft Foundry, Agent 365, Entra ID and the Graph API, plus a native Teams channel. If your company already runs on Microsoft identity and governance, the platform plugs into what you have.
AI engineering teams
Framework glue code is hard to review and harder to audit. ABL gives you Git-native, diffable agent definitions, a compiler that catches broken references before deployment, a CLI for CI pipelines and evals that act as quality gates. Agents move through development, staging and production like normal software.
System integrators
Partners build Kore.ai projects for clients in banking, travel and telecom. Industry solutions for banking, healthcare and retail, plus 100+ prebuilt service use cases, cut the starting effort for each client.
Kore.ai pricing
There is no price list on kore.ai. The old /pricing page now returns a 404, access runs through sales, and direct contracts are quote-based. The only public list prices come from Kore.ai’s own AWS Marketplace listings, where each product line is sold under a 12-month contract plus metered usage in US dollars. Treat them as a budgeting anchor, since negotiated deals can differ. Also plan for model costs: the platform uses the LLM provider credentials you register, so token charges come from that provider.
Kore.ai builds a custom proof-of-concept agent for your use case at no charge. It is a sales evaluation, not a free tier you can run in production.
Add-on units are billed per unit: Contact Center AI $0.10, Agent AI $0.20, Quality AI $0.05, Workforce Management $0.05, Interaction Gateway $0.065 ($0.015 without speech recognition and text-to-speech), and the BankAssist, HealthAssist and RetailAssist industry packs $0.15 each.
The ITAssist, HRAssist and RecruitAssist role packs each add $10 per user/month, and so does the AI for Process add-on.
$10,000 per AI agent per year under the contract, plus $0.02 per agent run (API call).
$40,000 each per 12 months, listed as separate contract lines for AI for Service, AI for Work and AI for Process.
Custom. Volume terms, private cloud, sovereign-region or on-premises deployment and implementation help are quoted by sales.
Kore.ai key features
Arch AI architect
You describe a goal in plain language or upload an SOP or design document, and Arch interviews you, drafts a blueprint and generates agents, workflows, tools, prompts and knowledge settings. It then runs an initial evaluation and keeps recommending fixes based on production traces.
Agent Blueprint Language (ABL)
Agent behavior, tools, guardrails, memory and handoffs live in a typed, YAML-based language that compiles to an intermediate representation and is validated before deployment. Six built-in orchestration patterns cover supervisor, delegation, handoff, fan-out, escalation and agent-to-agent federation. Because definitions are plain files, they can be diffed and reviewed in pull requests like any code.
Dual-brain runtime
Agentic reasoning and deterministic flows run in parallel through shared memory, authored in one language and governed by one runtime. Policies are enforced by the platform rather than by the model, so a prompt cannot talk an agent past a compliance rule. Scripted steps stay predictable while open questions still get flexible answers.
Observability, evals and Autoloop
The docs describe more than 200 trace events per session across reasoning, tool calls, guardrails and handoffs. Agent Evals test quality and safety with generated personas and edge cases, and Autoloop reruns optimization cycles against goals you define, both before launch and after real traffic arrives.
Model choice
The supported-models list spans OpenAI, Anthropic, Azure OpenAI, Microsoft Foundry, Google, AWS Bedrock, Vertex AI, Mistral, Cohere, Groq, DeepSeek, xAI and others, including realtime voice models. You can switch models without rebuilding agents, and workspace admins can set per-model token prices to track cost.
Channels and integrations
One agent definition can serve Slack, Microsoft Teams, WhatsApp, Messenger, Instagram, LINE, Telegram, Twilio SMS, email, Zendesk and Genesys, plus voice through realtime LLM voice, a classic speech pipeline, VXML IVR and AudioCodes. Kore.ai cites 40+ voice and digital channels and 300+ integrations, along with Web and Mobile SDKs, REST APIs and the A2A protocol.
Packaged applications
AI for Service adds agent assist with next-best actions and summaries, Quality AI that scores every conversation against custom criteria, and an AI-native contact center with agent and supervisor desktops. AI for Work adds permissioned enterprise search plus HR, IT and recruiting agents. These save you from building common use cases from scratch.
Kore.ai Pros & Cons
Pros
Kore.ai covers the whole agent lifecycle in one product: design with Arch, define in ABL, test with evals, deploy through environments and monitor with traces. Governance sits outside the model, which is exactly what security teams in banking and healthcare ask for, and the compliance list includes SOC 2 Type II, ISO 27001, PCI DSS and FedRAMP Moderate. You are not tied to one LLM, and deployment options run from Azure to on-premises. Reviewers on G2 and PeerSpot consistently praise the integrations, low-code building blocks and channel reach, and analysts named Kore.ai a Leader in Gartner and Forrester reports in 2026. Use a Proof Concierge build to check those claims against your own data.
Cons
This is not a tool you can try over a weekend. There is no self-serve free plan, sign-up is restricted to approved domains, and the AWS Marketplace contract lines alone reach tens of thousands of dollars before usage. G2 reviewers most often mention a steep learning curve, thin documentation for integrations and occasional lag or bugs in the builder, and some PeerSpot reviewers say support slows down after implementation. Artemis is also new: one recent G2 reviewer called it rushed and not yet developer-friendly, and a Gartner reviewer says private instances get features later. Budget for training through the Kore.ai Academy and ask for a migration plan if you run an older version.
Use Kore.ai if you want…
- Automate customer calls and chats with governed AI agents.
- Replace a legacy IVR with natural voice agents.
- Score every contact center conversation automatically for quality.
- Give employees one assistant for HR and IT requests.
- Search permissioned company knowledge across many connected systems.
- Generate agent blueprints from plain-language SOPs and requirements.
- Trace every agent decision for audits and compliance.
- Swap LLM providers without rebuilding your agents.
- Run agents on Azure, private cloud or on-premises.
Kore.ai alternatives
Kore.ai Reviews
G2 reviewers credit the platform with strong AI capabilities, smooth integrations and responsive support for enterprise conversational projects, while the most frequent complaint is a steep learning curve, especially around advanced features and debugging.
PeerSpot users like the low-code building blocks and the option to plug in different LLMs through an API, which makes testing faster than hand-coding; they also say the documentation lacks depth on integrations and that help after go-live can be slow.
An early G2 review of the Artemis edition welcomes its automation, architecture and evaluation concepts and its more deterministic behavior, but calls the platform not yet developer-friendly and rushed in places.
On Gartner Peer Insights, customers point to a large pool of ready-to-configure integrations and a supportive partnership, whereas a more critical reviewer says private-instance deployments lag behind on feature updates.
Integrators on G2 say Kore.ai makes complex IVR workflow design straightforward, though one firm had to train new staff itself because certification support for older versions was missing.
FAQ
Does Kore.ai have a free plan or free trial?
There is no self-serve free plan for the Artemis edition, and sign-up is enabled only for approved company domains. The free option is Proof Concierge, where Kore.ai builds a custom proof-of-concept agent for your use case at no charge.
How much does Kore.ai cost?
Direct pricing is quote-based. Kore.ai’s AWS Marketplace listings show AI for Service at $0.20 per session, AI for Work at $40 per user/month and AI for Process at $10,000 per agent per year, each under a 12-month contract with optional support and non-production lines.
What is Kore.ai Artemis?
Artemis is the new generation of the Kore.ai Agent Platform, launched on May 21, 2026. It introduced Agent Blueprint Language, the Arch AI architect and a dual-brain runtime, and it launched first on Microsoft Azure with other clouds to follow.
Which AI models does Kore.ai support?
The platform is model-agnostic and works with providers including OpenAI, Anthropic, Azure OpenAI, Google, AWS Bedrock, Mistral, Cohere, DeepSeek and xAI. You register your own provider credentials, so you can switch models without rebuilding agents.
Which channels can a Kore.ai agent use?
Agents can be deployed to web and mobile apps through SDKs, to Slack, Microsoft Teams, WhatsApp, Messenger, Instagram, Telegram, SMS and email, and to phone lines through voice channels and contact center connectors such as Genesys and AudioCodes.
Is Kore.ai suitable for regulated industries?
Kore.ai lists SOC 2 Type II, ISO 27001, PCI DSS and FedRAMP Moderate credentials, along with HIPAA alignment and GDPR compliance. It adds real-time PII tokenization, tenant isolation and audit trails, and it can be deployed in public cloud, sovereign regions, private cloud or on-premises.
Does Kore.ai offer an API and developer tools?
Yes. Developers get REST APIs, Web and Mobile SDKs, a CLI for build, test and deployment pipelines, and an MCP server that lets AI coding assistants such as Claude Code or Cursor build and manage projects.
Does Kore.ai support multiple languages?
Kore.ai advertises natural multilingual conversations with language switching mid-conversation. One published customer story describes a Fortune 100 financial institution handling 1.5 million voice interactions a year across 23 languages.
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