Threada vs. Kustomer AI
Kustomer AI focuses on CRM-native support and agent workflows. Threada is built for grounded website answers with citations, freshness controls, and strong embed security. Here is how they differ and how to combine them.
Comparison
| Dimension | Threada | Kustomer AI |
|---|---|---|
| Grounding | Hybrid RAG with citations and refusal policy | CRM data, macros, and flows |
| Freshness | Sitemap-first crawl, IndexNow, incremental recrawl | Updates tied to CRM data and content syncs |
| Analytics | Per-embed impressions, opens, chats, messages, fallback reasons | Conversation and agent metrics |
| Security | SRI, strict widget CSP, origin checks, SSO, formal threat model | CRM platform security; embed controls vary |
| Multi-tenant | Agency friendly styling and quotas per tenant | Single brand focus |
When Threada is the better fit
- Visitors want instant, cited answers on marketing, docs, or policy pages.
- Agencies manage multiple brands and need isolated styling, quotas, and analytics.
- Security teams demand strict CSP and origin validation for embeds.
- Ops teams want retrieval transparency and adaptive thresholds to curb hallucinations quickly.
When to rely on Kustomer
- Deep CRM workflows, case management, and agent collaboration drive support.
- Authenticated interactions require customer context that lives in Kustomer.
- Teams already tuned macros and flows inside Kustomer.
Running both
- Deploy Threada on public pages for grounded answers and citations.
- Keep Kustomer for account or ticket flows requiring CRM data.
- Use triggers to hand off account intents from Threada to Kustomer agents.
- Track containment, CSAT, and outdated feedback to adjust Threada crawl cadence and thresholds.
Grounded answers cut bounce on the open web while Kustomer remains the system of record for customer conversations.