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I want an AI to answer customer support tickets

AI customer support

Resolves common support tickets, deflects, and hands off to humans cleanly.

6 wrappers indexed · Category · support

Teardown

DECAGON

Customer Support AI

$4.5B

Wrapped product

Multi-channel support agent (voice/chat/email)

Same connectors + frontier LLM agent + retrieval on your support data

Backers

  • Andreessen Horowitz
  • Accel
  • Coatue
  • Index Ventures
Build it yourself →

Teardown

ADA

Customer Support

$130M

Wrapped product

Multi-channel AI agent platform for customer support automation

Same connectors + frontier LLM + retrieval — needs routing orchestration

Backers

  • Spark Capital
  • Accel
  • Bessemer Venture Partners
Build it yourself →

Teardown

SIERRA

Customer Support AI

$4.5B

Wrapped product

Multichannel AI support agents with enterprise compliance

Same knowledge retrieval + frontier LLM + handoff rules — lacks enterprise deployment trust

Backers

  • Sequoia Capital
  • Benchmark
  • ICONIQ Capital
  • Thrive Capital
Build it yourself →

Teardown

CRESCENDO

Customer Support AI

$500M

Wrapped product

Managed AI + BPO support with performance guarantee

Same helpdesk connectors + frontier LLM + internal agent team on your data

Backers

  • General Catalyst
Build it yourself →

Teardown

MAVEN AGI

Customer Support AI

$50M

Wrapped product

Autonomous support agent with deep CRM integration

Same connectors + agent API on your CRM data — heavier integration, weaker workflow tuning

Build it yourself →

Teardown

POLYAI

Voice AI

$50M

Wrapped product

Omnichannel voice/chat/SMS agent platform, per-minute pricing

Same CRM connectors + LLM + open TTS — rollout posture is yours to build

Backers

  • NVIDIA
  • Khosla Ventures
Build it yourself →

Then build it yourself

Most of the value is the same APIs + your data + a clean prompt.

Open any teardown above for the data layer, the agent prompt, and the exact internal substitute. The point isn't to clone the startup — it's to replay the useful workflow inside your org.