Decagon vs Harvey AI: 2026 comparison
Conversational support agents that resolve tickets like your best reps.
Decagon vs Harvey AI — specs
| Spec | Decagon | Harvey AI |
|---|---|---|
| Agent Rank | 72 / 100 (A) | 67 / 100 (B) |
| Autonomy | Autonomous | Semi-autonomous |
| Pricing | Subscription · Free tier | Subscription · Free tier |
| Open source | No | No |
| Capabilities | Tool use, Memory, RAG | RAG, Memory, Tool use |
| Integrations | 3 apps | 3 apps |
| Verified | Verified | Verified |
| Released | Apr 2025 | Apr 2025 |
Agent Rank breakdown
- 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?
- Autonomy fit
- 8
- Capabilities
- 6
- Integrations
- 2
- 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?
Pros & cons
- +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
- −Voice support exists but is not the strength
- −Sales-led — no self-serve sign-up
- −Per-resolution pricing can sting if tickets spike unexpectedly
- +Highest-quality legal-domain AI in 2026 — trained on actual legal work
- +Used by 350+ AmLaw firms; battle-tested in real matters
- +Strict data isolation — work product never leaves customer tenancy
- −Enterprise pricing only — no transparent SaaS pricing
- −Sales cycle is months; not a self-serve product
- −Still a junior associate by capability — humans own final work product
Pricing
- +Per-resolution pricing
- +Zendesk / Intercom integration
- +Onboarding included
- +Custom integrations
- +SSO + audit log
- +Dedicated CSM
- +AI legal associate
- +Trained on legal corpora
- +iManage / NetDocs integration
- +SOC 2 II + ISO 27001
- +Everything in Firm
- +Dedicated VPC
- +Custom workflows
- +Privileged-data isolation
Which one should you pick?
Pick Decagon if you want the highest autonomy and the verification loop is in place.
Try Decagon →Pick Harvey AI if its specific capabilities (RAG, Memory) match what you need.
Try Harvey AI →Affiliate links. We may earn a commission at no extra cost to you.
Frequently asked
Should I pick Decagon or Harvey AI in 2026?+
Pick Decagon if you want the highest autonomy and the verification loop is in place. Pick Harvey AI if its specific capabilities (RAG, Memory) match what you need. Most working teams running both can use Decagon for primary work and Harvey AI for the workflows where its specific strengths matter.
What's the price difference between Decagon and Harvey AI?+
Both Decagon and Harvey AI start in the same pricing range (Subscription · Free tier vs Subscription · Free tier). Total cost of ownership depends on your team size and volume — see the TCO calculator for your specific math.
Which is more autonomous, Decagon or Harvey AI?+
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.