Threada vs. Verloop AI
Verloop AI focuses on intent-based automation across channels. Threada is built for grounded website answers with citations, freshness controls, and hardened embeds. Here is how they differ and how to run them together.
Comparison
| Dimension | Threada | Verloop AI |
|---|---|---|
| Grounding | Hybrid RAG with refusal policy and citations | Intents, flows, and FAQs |
| Freshness | Sitemap-first crawl, IndexNow, incremental recrawl | Dependent on updated intents and knowledge |
| Analytics | Per-embed impressions, opens, chats, messages, fallback reasons | Conversation and flow metrics |
| Security | SRI, strict widget CSP, origin checks, SSO, formal threat model | Platform security; embed headers depend on setup |
| Multi-tenant | Agency friendly styling and quotas per tenant | Single brand focus |
When Threada fits best
- Visitors want cited answers on marketing, docs, or pricing pages.
- Agencies manage multiple brands and need isolated styling, quotas, and analytics.
- Security teams require strict CSP and origin validation for embeds.
- Ops wants retrieval transparency to reduce hallucinations quickly.
When to lean on Verloop
- Transactional flows and messaging across channels are central.
- Existing investments in intent training and connectors.
- Scenarios that need backend actions beyond simple Q&A.
Pairing both
- Deploy Threada on public pages for grounded Q&A with citations.
- Keep Verloop for transactional flows and messaging channels.
- Route account or transactional intents from Threada to Verloop when flows are better suited.
- Monitor Threada fallback reasons to decide which intents to model in Verloop.
Grounded answers and intent automation cover different needs. Pairing Threada with Verloop gives visitors fast, trustworthy responses while complex actions run in dedicated flows.