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Kore.ai

Enterprise platform to build and run production AI agents

Agent PlatformSupervised

Last reviewed 2026-06-19

Kore.ai is an enterprise conversational and agentic AI vendor that gives large organizations a single platform to build, deploy, and operate production AI agents. Its foundation is an infrastructure- and model-agnostic agent platform with no-code and pro-code tooling, multi-agent orchestration, enterprise search and RAG, and runtime-enforced guardrails. On top sit three packaged suites: AI for Service (customer service and agentic contact center), AI for Work (employee productivity, enterprise search, and 200+ prebuilt agent templates), and AI for Process (automation of knowledge-intensive processes), plus GALE, a generative-AI app platform with a no-code builder and a model hub. The platform is explicitly model-agnostic: teams can plug in commercial LLMs, open-source models, or bring their own, plus platform-hosted models. It is delivered primarily as SaaS with on-premise and behind-firewall options for regulated environments, plus SSO/SAML and audit logging. It targets large enterprises in regulated, high-volume sectors. Kore.ai frames autonomy as bounded and governed with human-in-the-loop, so it tops out at supervised-agent here.

What it can do

  • Automate customer service across voice and chat

    Supervised

    Runs an agentic contact center with agent assist and QA, resolving interactions across voice and chat.

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  • Execute multi-step business processes

    Supervised

    Automates knowledge-intensive processes end to end across enterprise systems with bounded, governed autonomy.

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  • Unify search and automate HR/IT workflows

    Copilot

    Provides enterprise search and 200+ prebuilt agents for HR, IT, finance, and legal employee tasks.

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  • Orchestrate multiple agents over open protocols

    Supervised

    Runs multiple agents in parallel and ingests third-party agents via A2A and MCP.

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Strengths

  • +Genuinely model- and infrastructure-agnostic with bring-your-own-model
  • +Deep enterprise readiness: SSO/SAML, on-prem and behind-firewall, encryption, audit, runtime policy
  • +Broad packaged offering (Service, Work, Process, GALE) with open-protocol (A2A, MCP) interoperability

Limitations

  • Opaque, sales-gated, session-based pricing with add-ons
  • Breadth brings complexity; not lightweight for small teams
  • Marketed autonomy is bounded and governed with human-in-the-loop

Overview

Kore.ai is an enterprise platform to build and run production AI agents, with an agent platform foundation and three packaged suites (Service, Work, Process) plus GALE for generative-AI apps.

What it does

It automates customer service in an agentic contact center (supervised), executes multi-step processes with governed autonomy (supervised), unifies enterprise search and HR/IT workflows via 200+ prebuilt agents (copilot), and orchestrates multiple agents over A2A and MCP (supervised).

Integrations & setup

SaaS plus on-prem and behind-firewall options, with connectors to AWS, Azure, Slack, Teams, and identity providers, and open protocols (A2A, MCP, REST).

Pricing

Custom enterprise, quote-based, with usage priced per interaction session. No public list pricing.

Best for / not for

Best for large, regulated enterprises that need governance, on-prem options, and model flexibility at scale. Overkill for small teams.

Alternatives

Yellow.ai and Ada are enterprise conversational AI peers; Sierra targets autonomous customer support.

What people are saying

We aggregate real LinkedIn discussion into sentiment for the agents people search most. Kore.ai isn't tracked yet, want it added? Request tracking.

FAQ

Can Kore.ai run on-premise?+

Yes. It is primarily SaaS but offers on-premise and behind-firewall deployment via secure connectors for regulated environments, along with SSO/SAML, encryption, and audit logging.

Is Kore.ai locked to one LLM?+

No. It is model-agnostic: you can use commercial LLMs, open-source models, bring your own via compatible APIs, or use platform-hosted models from its model hub.

Sources

Last reviewed 2026-06-19

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