Tidio Lyro vs Decagon
A detailed side-by-side comparison to help you choose the right AI customer support agent for your needs.
Best for e-commerce with Claude-powered conversations
Tidio Lyro
Tidio Lyro is powered by Anthropic's Claude models, providing sophisticated conversational AI with strong reasoning capabilities and nuanced understanding of customer intent. The AI answers customer q...
AI Models
Claude (Anthropic)Tidio proprietary training
Key Features
- Claude-powered conversations with advanced reasoning
- Answers from FAQ/knowledge base in seconds
- Learns from every interaction continuously
- Seamless handoff to humans with full context
- 12 language support with auto-detection
Pricing
Starter — $24/month
Growth — $49/month
Plus — $749/month
Lyro AI Add-on — $0.50/conversation
Pros
- Claude provides superior conversation quality
- E-commerce integrations enable order-specific support
- Visual builder accessible to non-technical users
Cons
- Lower conversation limits on cheaper plans
- Best suited for e-commerce, less versatile for other industries
Best for enterprise AI agents handling complex, multi-system support workflows
Decagon
Decagon builds enterprise AI agents designed specifically for complex customer support workflows where resolving a single ticket may require interacting with multiple backend systems, applying nuanced...
AI Models
GPT-4oClaudeProprietary fine-tuned enterprise models
Key Features
- Complex multi-system workflow execution across CRMs, billing, and databases
- Full support history training including edge cases and escalations
- Policy engine for encoding business rules without engineering resources
- Full conversation lifecycle handling from inquiry to resolution confirmation
- Human benchmark comparison on accuracy and satisfaction metrics
Pricing
Enterprise — Custom pricing
Pros
- Handles genuinely complex enterprise workflows that simpler tools cannot
- Policy engine lets operations teams configure agent behavior without engineers
- Human benchmark reporting provides honest performance transparency
Cons
- Enterprise-only positioning excludes smaller companies
- Deep integration setup requires meaningful implementation investment