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Decagon vs Linear Agent: 2026 comparison

Conversational support agents that resolve tickets like your best reps.

🎧SupportAutonomousSubscription
Tool useMemoryRAG

AI agent inside Linear — triages issues, drafts engineering specs, runs cross-team workflows on tickets.

⚙️OpsSemi-autonomousSubscription · from $8
Tool useRAGMemory

Decagon vs Linear Agent — specs

SpecDecagonLinear Agent
Agent Rank72 / 100 (A)72 / 100 (A)
AutonomyAutonomousSemi-autonomous
PricingSubscription · Free tierSubscription · from $8
Open sourceNoNo
CapabilitiesTool use, Memory, RAGTool use, RAG, Memory
Integrations3 apps3 apps
VerifiedVerifiedVerified
ReleasedApr 2025Apr 2025

Categories: DecagonSupport · Linear AgentOps

Agent Rank breakdown

Decagon
Agent Rank
72/ 100
AA-tier
Autonomy fit
9
Capabilities
6
Integrations
4
Pricing value
9
Polish & maturity
5
Verifiability
10

Auto-computed from autonomy, capabilities, integrations, pricing, maturity and editorial verification. Updated every deploy. How is this computed?

Linear Agent
Agent Rank
72/ 100
AA-tier
Autonomy fit
8
Capabilities
6
Integrations
6
Pricing value
8
Polish & maturity
5
Verifiability
10

Auto-computed from autonomy, capabilities, integrations, pricing, maturity and editorial verification. Updated every deploy. How is this computed?

Pros & cons

Decagon
Pros
  • +Chat-first agent with consistently 65–75% tier-1 deflection in production
  • +Deep integration with existing helpdesks (Zendesk / Intercom / Salesforce)
  • +Mid-market priced — easier conversation than Sierra
Cons
  • Voice support exists but is not the strength
  • Sales-led — no self-serve sign-up
  • Per-resolution pricing can sting if tickets spike unexpectedly
Linear Agent
Pros
  • +Native to Linear — zero extra setup for teams already using it
  • +Triage and spec-drafting genuinely save time on issue grooming
  • +Pricing folds AI features into the existing Linear seat
Cons
  • Only useful if you live in Linear
  • Less powerful than dedicated coding agents (Cursor, Claude Code) for code work
  • Agent autonomy bounded by Linear-specific tasks

Pricing

Decagon
Growth
Custom
Mid-market
  • +Per-resolution pricing
  • +Zendesk / Intercom integration
  • +Onboarding included
Recommended
Enterprise
Custom
Enterprise
  • +Custom integrations
  • +SSO + audit log
  • +Dedicated CSM
Linear Agent
Free
Free
Small teams (≤10 users)
  • +Basic Linear
  • +Limited AI features
Recommended
Standard
$8/seat/mo
Growing teams
  • +Full Linear + AI Agent
  • +Issue triage
  • +Spec drafting
Business
$14/seat/mo
Larger orgs
  • +SAML SSO
  • +SCIM
  • +Advanced analytics

Which one should you pick?

Decagon

Pick Decagon if cost is the main constraint or if you want the highest autonomy and the verification loop is in place.

Try Decagon →
Linear Agent

Pick Linear Agent if its specific capabilities (Tool use, RAG) match what you need.

Try Linear Agent →

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Frequently asked

Should I pick Decagon or Linear Agent in 2026?+

Pick Decagon if cost is the main constraint or if you want the highest autonomy and the verification loop is in place. Pick Linear Agent if its specific capabilities (Tool use, RAG) match what you need. Most working teams running both can use Decagon for primary work and Linear Agent for the workflows where its specific strengths matter.

What's the price difference between Decagon and Linear Agent?+

Decagon starts at Subscription · Free tier; Linear Agent starts at Subscription · from $8. Decagon is the cheaper entry option. For team deployments the TCO can differ — use the AI Agent Rank TCO calculator for your specific volume.

Which is more autonomous, Decagon or Linear Agent?+

Decagon is the more autonomous of the two (Autonomous vs Semi-autonomous). Higher autonomy ships throughput faster but requires verification loops in place — see our autonomous-vs-copilot framing for when each tier wins.

Want the real monthly cost at your volume? Run the TCO calculator →
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