Axari vs Medley: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Axari and Medley — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Axari

Paid

An AI workforce for cybersecurity teams — an "AI twin" that triages alerts, chases owners and collects compliance evidence 24/7.

Critical Exposure Protection: Pulls finding and asset context, creates and assigns the ticket, then re-checks the scanner so an exposure is only closed once it is actually gone.
Continuous Compliance: Collects access evidence, maps it to controls and chases owners who have not responded, keeping evidence current outside of audit week.
Vendor Onboarding and Risk Review: Requests missing vendor documents, scores the vendor against internal policy and routes the decision to the risk owner with approvals attached.
Security Questionnaire Acceleration: Drafts answers from a team's approved response library and current policy language, flagging only the items that need human judgement.
Access Assurance: Enumerates every account and entitlement, nudges reviewers against a cutoff, then revokes and verifies removal rather than just requesting it.
Threat Response Assurance: Groups overnight alerts, enriches them with endpoint telemetry and opens assigned investigations so nothing sits in a queue.
Earned Access and Audit Trail: Every action requires human approval and is logged end to end, with zero data retention and customer knowledge staying with the customer.
Tool-Agnostic Integration: Works on top of a team's existing security stack instead of replacing it, mapping each tool's role during the first day of onboarding.

Alert Triage Coverage: Extending a small SOC to 24/7 by having the twin group, enrich and open overnight investigations before the team logs on.
Audit Readiness: Keeping SOC 2 or ISO evidence continuously collected and mapped to controls instead of scrambling during audit week.
Vulnerability Remediation Follow-Through: Driving findings to a verified fix by chasing the owning service team and confirming the scanner is clear.
User Access Reviews: Running periodic entitlement reviews end to end, including reviewer nudges and verified revocation.
Security Deal Support: Turning around customer security questionnaires quickly so enterprise deals are not blocked on review cycles.
Third-Party Risk Management: Onboarding new vendors with policy-scored documentation and a documented risk decision.
Incident Coordination: Keeping containment steps, session revocation and legal or leadership updates on a single coordinated timeline.

Free

Claude Code plugin that decomposes prompts into coordinated multi-agent plans and visualizes the plan at a shareable URL.

Slash-Command Integration: Activates directly inside Claude Code via the /mission command to produce a plan without leaving the chat interface.
Prompt Decomposition: Breaks a single user prompt into discrete subtasks with clear dependencies to turn vague requests into actionable steps.
Multi-Agent Coordination: Generates a coordinated plan that assigns roles or agent responsibilities and sequences work across multiple agents to tackle complex tasks.
Plan Visualization URL: Renders the produced plan structure at a shareable URL so users can inspect, review, and share the full task graph and execution plan.
Task Assignment & Sequencing: Determines ordering and handoffs between subtasks so parallel and dependent work is organized for execution by different agents.
Shareable Workflow Export: Enables distribution of the decomposed plan via link for collaboration, review, or external execution tracking.
Decomposes a single prompt into a coordinated multi-agent plan
Invoked within Claude Code via the /mission command
Generates a structured plan view accessible at a shareable URL
Orchestrates multiple agents/subtasks rather than relying on a single model
Focus on readable plan structure for inspection and collaboration

Complex Project Breakdown: Converting a high-level product or research brief into a multi-step plan with assigned agent roles and dependencies for coordinated execution.
Multi-step Code Development: Decomposing a feature request into design, implementation, testing, and deployment tasks that can be executed or reviewed by specialized agents.
Data Analysis Pipelines: Breaking down an analysis prompt into data-cleaning, transformation, modeling, and visualization subtasks that are assigned and sequenced.
Content Creation Workflows: Orchestrating ideation, drafting, editing, fact-checking, and formatting steps across different agents to produce polished content.
Collaborative Review & Handoff: Sharing the generated plan URL with teammates or stakeholders to review responsibilities, timelines, and handoffs before execution.
Experiment Orchestration: Designing and coordinating multi-step experiments or research tasks where different agents perform measurements, aggregation, and interpretation.
Breaking complex prompts into executable subtasks for multi-agent workflows
Orchestrating LLM agents to collaborate on a single objective
Sharing and reviewing decomposition and task assignments via a URL
Improving reliability and coverage by distributing work across multiple agents
Prompt engineering for complex, multi-step automation tasks