Agentic Index
Fin vs Lorikeet (2026)
Both charge per resolution at a similar rate and they serve different risk profiles, at 11 and 11 of 14. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Fin is 0.99 per resolution with knowledge grounding, multichannel support and simulation based testing. Lorikeet is roughly 0.80 per resolution, built for regulated fintech and health technology, running multi step actions across chat, email, voice and SMS with 100 percent quality assurance and full audit. Twenty cents difference per resolution is noise; 100 percent quality assurance on every conversation is not, and if you are regulated that is the whole comparison.
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Fin and Lorikeet 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 Fin if
- Documented coverage is slightly broader and simulation testing before launch is the safeguard you want.
- You already use Intercom and the integration is effectively free.
- Your support is not regulated, so audit depth is not worth paying for.
Choose Lorikeet if
- You are in regulated fintech or health technology and every conversation must be reviewable.
- 100 percent quality assurance rather than sampling is the compliance posture you need.
- Multi step actions across voice and SMS alongside chat is the channel range.
| At a glance | Fin | Lorikeet |
|---|---|---|
| Category | Customer support agent | Customer support agent |
| Entry price | $0.99 per outcome | ~$0.80/resolution (Scale: 48k/$48k yr) |
| Free / trial | 14-day free trial | — |
| Pricing confidence | public exact | public partial |
| Feature | F Fin |
L Lorikeet |
|---|---|---|
| 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. |
Partial | Partial |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Full / Explicit | 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. |
Partial | Full / Explicit |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
Full / Explicit | 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. |
Full / Explicit | Partial |
| 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. |
No / Not documented | Partial |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Full / Explicit | Partial |
|
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 | F Fin |
L Lorikeet |
|---|---|---|
|
Entry price Lowest public entry point |
$0.99 per outcome | ~$0.80/resolution (Scale: 48k/$48k yr) |
|
Pricing confidence How public the numbers are |
Public, exact | Public, partial |
|
Billing Primary billing axis |
outcomes | resolutions |
|
Variable cost Workload / overage exposure |
High variable cost | Medium variable cost |
|
Free tier / trial Try before you buy |
No free tierTrial
|
No free tier
|
|
Buying motion Self-serve vs sales call |
Mixed | Sales call |
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