Agentic Index
Decagon vs Kore.ai (2026)
Both serve enterprise support and they sit at different points of the build against buy line, at 10 and 13 of 14. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Kore is a platform with 200 plus templates, 300 plus integrations and voice plus chat, free tier then pay as you go. Decagon is purpose built for customer support with deep integration into support toolchains, sold through enterprise engagement. Kore documents more and is broader; Decagon is narrower and goes deeper into the tools your support team already lives in.
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Decagon and Kore.ai are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 969 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Decagon if
- Deep integration into your existing support toolchain is what determines whether this works.
- You want a support product rather than a general conversational platform.
- Purpose built for support means fewer decisions to make during deployment.
Choose Kore.ai if
- Documented coverage is materially deeper and integration breadth is the requirement.
- A free tier and pay as you go lets you evaluate before committing.
- Use cases beyond customer support are on your roadmap.
| At a glance | Decagon | Kore.ai |
|---|---|---|
| Category | Customer support agent | Customer support agent |
| Entry price | Contact sales | Free tier (~5,000 requests/mo) · Standard pay-as-you-go $0.20/conversation ($100 min, $500 signup credits) · Enterprise custom (session-based) |
| Free / trial | n/p | — |
| Pricing confidence | contact only | public partial |
| Feature | D Decagon |
K Kore.ai |
|---|---|---|
| Action & orchestration | ||
|
Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
Full / Explicit | Full / Explicit |
|
Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
Full / Explicit | Full / Explicit |
|
Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
Full / Explicit | Full / Explicit |
| Knowledge & context | ||
|
Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
Full / Explicit | Full / Explicit |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Full / Explicit | Full / Explicit |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Partial | Full / Explicit |
|
Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
Full / Explicit | Full / Explicit |
|
Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
Full / Explicit | Full / Explicit |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
Partial | Full / Explicit |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
No / Not documented | Full / Explicit |
| Platform extensibility | ||
|
Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
Partial | Full / Explicit |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Partial | Full / Explicit |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
Full / Explicit | Full / Explicit |
| Specialist automation | ||
|
Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
No / Not documented | No / Not documented |
Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | D Decagon |
K Kore.ai |
|---|---|---|
|
Entry price Lowest public entry point |
Contact sales | Free tier (~5,000 requests/mo) · Standard pay-as-you-go $0.20/conversation ($100 min, $500 signup credits) · Enterprise custom (session-based) |
|
Pricing confidence How public the numbers are |
Contact only | Public, partial |
|
Billing Primary billing axis |
hybrid | hybrid |
|
Variable cost Workload / overage exposure |
High variable cost | Medium variable cost |
|
Free tier / trial Try before you buy |
No free tier
|
Free tierTrial
|
|
Buying motion Self-serve vs sales call |
Sales call | Mixed |
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