Customer Experience AI
Decagon vs Retell AI.
Both sit in Customer Experience AI, scored on the same six pillars from the same published methodology. Here is where they actually differ.
The short answer
Too close to call on score alone — Decagon sits at 82.7 and Retell AI at 82.0. A gap that size is inside the noise of any honest scoring model, so pick on fit rather than rank.
Decagon leads on capability and security & compliance; Retell AI leads on value for money.
Decagon AI
82.7
Excellent
AI support agents your CX team programs in plain English.
- From
- Custom (per-conversation pricing)
- Pricing
- Enterprise
- Maturity
- Emerging
- Founded
- 2023
Retell AI
82.0
Excellent
Production voice AI agents in days, priced per minute.
- From
- From ~$0.07 per minute + LLM/telephony
- Pricing
- Usage-based
- Maturity
- Emerging
- Founded
- 2023
Pillar by pillar
The same six pillars and fixed weights used for every tool on the site. A lead of fewer than 5 points is not called for either side — these are evidence-backed judgements, not measurements. Read the methodology.
Capability
Decagon by 6
Value for Money
Retell AI by 17
Security & Compliance
Decagon by 6
Integrations & Ecosystem
Level
Maturity & Reliability
Level
Momentum
Level
Which one, and when
Pick Decagon if
- →the hardest end of the work is what you are buying for — it leads Capability by 6 points.
- →compliance and data control decide it — it leads Security & Compliance by 6 points.
- →CX teams wanting hands-on control
- →High-volume support automation
- →Chat-first support with voice expansion
The catch
- Initial setup requires engineering involvement
- No public pricing; per-conversation costs need volume modeling
Pick Retell AI if
- →cost per unit of output is the binding constraint — it leads Value for Money by 17 points.
- →SMB and mid-market call automation
- →Appointment booking & routing
- →Teams with developers who want control
The catch
- Autonomous handling focus; thinner agent-assist tooling
- Younger enterprise compliance story than CCaaS suites
What each is good at
Decagon
- ✓AOPs let non-engineers write and iterate agent logic in plain English
- ✓Direct workflow control after initial engineering setup
- ✓Rapid enterprise traction across support-heavy industries
Retell AI
- ✓Transparent per-minute pricing, model costs before you commit
- ✓Fastest path to production voice agents (days, not quarters)
- ✓Developer-grade APIs with full conversation control
Other comparisons in Customer Experience AI
Comparing something else? Build your own side-by-side across any tools in the catalog.