Agentic Index
Gradient Labs vs Lorikeet (2026)
Gradient Labs and Lorikeet both target regulated, high stakes support, and the split is procedure driven autonomy versus audited action taking: Gradient Labs runs an agent, Otto, that follows procedures across disputes, KYC, lending, fraud, and support, while Lorikeet handles multi step actions across chat, email, voice, and SMS with 100 percent quality assurance and audit at about 80 cents per resolution. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Gradient Labs is contact sales. Both suit fintech and healthtech, so weigh procedure control against audited resolution pricing.
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Gradient Labs 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 956 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Gradient Labs if
- You want an agent that follows defined procedures across disputes, KYC, lending, and fraud.
- Procedure driven behavior in a regulated financial context is your priority.
- You are comfortable with contact sales for a vertical specific agent.
Choose Lorikeet if
- You want multi step actions across chat, email, voice, and SMS with full quality assurance and audit.
- Resolution based pricing at about 80 cents per resolution fits how you buy.
- Auditability on every conversation is a hard requirement.
| At a glance | Gradient Labs | Lorikeet |
|---|---|---|
| Category | Customer support agent | Customer support agent |
| Entry price | Contact for pricing | ~$0.80/resolution (Scale: 48k/$48k yr) |
| Free / trial | — | — |
| Pricing confidence | contact only | public partial |
| Feature | G Gradient Labs |
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. |
Partial | 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. |
Partial | 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. |
Unknown / Unspecified | 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. |
No / Not documented | Partial |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
No / Not documented | 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 | G Gradient Labs |
L Lorikeet |
|---|---|---|
|
Entry price Lowest public entry point |
Contact for pricing | ~$0.80/resolution (Scale: 48k/$48k yr) |
|
Pricing confidence How public the numbers are |
Contact only | Public, partial |
|
Billing Primary billing axis |
— | resolutions |
|
Variable cost Workload / overage exposure |
High variable cost | Medium variable cost |
|
Free tier / trial Try before you buy |
No free tier
|
No free tier
|
|
Buying motion Self-serve vs sales call |
— | Sales call |
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