Skip to main content

Decagon vs Vapi

A detailed side-by-side comparison to help you choose the right AI customer support agent for your needs.

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
EnterpriseCustom 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
Best voice AI infrastructure for developers building phone-based AI agents

Vapi

Vapi is the leading voice agent infrastructure for developers — a platform you wire into your phone system to deploy AI agents that handle calls, take orders, qualify leads, and execute customer-suppo...

AI Models
GPT-4 / GPT-5Claude familyGeminiCustom (BYO)
Key Features
  • Real-time voice agent infrastructure (sub-500ms latency)
  • Bring-your-own LLM (OpenAI, Anthropic, custom endpoints)
  • Bring-your-own voice (ElevenLabs, OpenAI, custom clones)
  • Bring-your-own telephony (Twilio, Vonage, SIP)
  • Tool calling for CRM / database / API actions
Pricing
Free trial$10 credit
Pay-as-you-go~$0.05-$0.20/minute
EnterpriseCustom
Pros
  • Best-in-class latency (<500ms) makes voice agents feel natural
  • Bring-your-own everything (LLM, voice, telephony) — no vendor lock-in
  • Pay-as-you-go pricing scales with usage, no upfront commitment
Cons
  • Developer-facing — non-technical buyers should look at Sierra / Decagon
  • Per-minute costs add up at scale (typical mid-volume: $5K-$30K/mo)

Verdict: Decagon vs Vapi

Pick Decagon if you need enterprise ai agents handling complex, multi-system support workflows. Pick Vapi if you need voice ai infrastructure for developers building phone-based ai agents.

More AI models

Vapi supports 4 models.

Who should buy this

Decagon

Best for
  • Enterprise CX team replacing tier-1 ticket volume with autonomous agents
  • Mid-market support org with deep multi-system workflow needs (CRM + billing + product)
  • Ops team that wants to encode policies (refund eligibility, SLA tiers) without engineering
Not ideal for
  • SMBs or early-stage startups (enterprise-only positioning)
  • Teams needing self-serve onboarding (sales-led + implementation services)
Realistic monthly cost

Enterprise contracts (custom). Typical mid-market starting commitment ~$60-120K/yr based on conversation volume.

Verified 2026-05-02

Vapi

Best for
  • Developer building voice AI as a product feature (receptionist, scheduler, qualifier)
  • Startup with phone-heavy customer interaction (food, healthcare, real estate)
  • Engineering team wanting BYOL LLM control over voice agent stack
Not ideal for
  • Non-technical buyers wanting an out-of-box CX platform (Sierra / Decagon better)
  • Buyers without dev resources to wire BYOL pipeline
Realistic monthly cost

Free $10 trial. Indie dev / small deployment: $50-$500/mo. Mid-volume voice agent fleet: $5K-$30K/mo. Enterprise: custom contracts.

Verified 2026-05-03

Capabilities at a glance

CapabilityDecagonVapi
Multi-system workflow execution
CRM + billing + DB + custom APIs
Policy / business-rule engine
Agent Operating Procedures
Voice channel
Chat / email channel
Self-serve signup
Human-in-the-loop escalation
Real-time voice pipeline (STT + LLM + TTS)
<500ms latency
Bring-your-own LLM
Bring-your-own voice
Bring-your-own telephony
Tool calling in voice agents
50+ language support
BAA for HIPAA
Enterprise
On-prem / self-hosted
Supported Partial Not supported No data

Security & compliance

Standard / controlDecagonVapi
SOC 2
Type II
Type II
HIPAA
GDPR
SSO / SAML
RBAC
Audit logs
Trains on customer data
No
No
Decagon verified at trust.decagon.aiVapi verified at vapi.ai

What users say

Decagon

Notable customers

Chime, Duolingo, ClassPass, Hunter Douglas, Rippling, Noom

Vapi

Reddit sentiment: Positive
Notable customers

Y Combinator-backed voice AI startups, Healthcare scheduling apps, Restaurant ordering systems

Frequently asked questions

What AI models do Decagon and Vapi use?+

Decagon runs on GPT-4o, Claude, Proprietary fine-tuned enterprise models. Vapi runs on GPT-4 / GPT-5, Claude family, Gemini, Custom (BYO).

What is the main difference between Decagon and Vapi?+

Decagon is positioned as best for enterprise ai agents handling complex, multi-system support workflows, while Vapi is positioned as best voice ai infrastructure for developers building phone-based ai agents. Pick the one whose strength aligns with your primary use case.

Which has better integrations, Decagon or Vapi?+

Decagon integrates with Salesforce, Zendesk, Rippling, Stripe and 3 more. Vapi integrates with Twilio, Vonage, OpenAI, Anthropic and 3 more.

What are the main weaknesses of Decagon and Vapi?+

Decagon's main drawback: enterprise-only positioning excludes smaller companies. Vapi's main drawback: developer-facing — non-technical buyers should look at sierra / decagon.

Are Decagon and Vapi worth it in 2026?+

Both remain competitive customer support options in 2026. Decagon stands out for handles genuinely complex enterprise workflows that simpler tools cannot. Vapi stands out for best-in-class latency (<500ms) makes voice agents feel natural. Choose based on which trade-offs fit your workflow and budget.